index
int64 | repo_id
string | file_path
string | content
string |
|---|---|---|---|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/ParseV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ParseV3 extends RequestSchemaV3 {
/**
* Final frame name
*/
@SerializedName("destination_frame")
public FrameKeyV3 destinationFrame;
/**
* Source frames
*/
@SerializedName("source_frames")
public FrameKeyV3[] sourceFrames;
/**
* Parser type
*/
@SerializedName("parse_type")
public ApiParseTypeValuesProvider parseType;
/**
* Field separator
*/
public byte separator;
/**
* Single Quotes
*/
@SerializedName("single_quotes")
public boolean singleQuotes;
/**
* Check header: 0 means guess, +1 means 1st line is header not data, -1 means 1st line is data not header
*/
@SerializedName("check_header")
public int checkHeader;
/**
* Number of columns
*/
@SerializedName("number_columns")
public int numberColumns;
/**
* Column names
*/
@SerializedName("column_names")
public String[] columnNames;
/**
* Value types for columns
*/
@SerializedName("column_types")
public String[] columnTypes;
/**
* Skipped columns indices
*/
@SerializedName("skipped_columns")
public int[] skippedColumns;
/**
* If true, will force the column types to be either the ones in Parquet schema for Parquet files or the ones
* specified in column_types. This parameter is used for numerical columns only. Other columnsettings will happen
* without setting this parameter. Defaults to false.
*/
@SerializedName("force_col_types")
public boolean forceColTypes;
/**
* Domains for categorical columns
*/
public String[][] domains;
/**
* NA strings for columns
*/
@SerializedName("na_strings")
public String[][] naStrings;
/**
* Size of individual parse tasks
*/
@SerializedName("chunk_size")
public int chunkSize;
/**
* Delete input key after parse
*/
@SerializedName("delete_on_done")
public boolean deleteOnDone;
/**
* Block until the parse completes (as opposed to returning early and requiring polling
*/
public boolean blocking;
/**
* Key-reference to an initialized instance of a Decryption Tool
*/
@SerializedName("decrypt_tool")
public DecryptionToolKeyV3 decryptTool;
/**
* Custom characters to be treated as non-data line markers
*/
@SerializedName("custom_non_data_line_markers")
public String customNonDataLineMarkers;
/**
* Name of the column the persisted dataset has been partitioned by.
*/
@SerializedName("partition_by")
public String[] partitionBy;
/**
* Parse job
*/
public JobV3 job;
/**
* Rows
*/
public long rows;
/**
* One ASCII character used to escape other characters.
*/
public byte escapechar;
/**
* Adjust the imported time from GMT timezone to cluster timezone.
*/
@SerializedName("tz_adjust_to_local")
public boolean tzAdjustToLocal;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public ParseV3() {
separator = 0;
singleQuotes = false;
checkHeader = 0;
numberColumns = 0;
forceColTypes = false;
chunkSize = 0;
deleteOnDone = false;
blocking = false;
customNonDataLineMarkers = "";
rows = 0L;
escapechar = 0;
tzAdjustToLocal = false;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/PartialDependenceKeyV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class PartialDependenceKeyV3 extends KeyV3 {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Name (string representation) for this Key.
public String name;
// Name (string representation) for the type of Keyed this Key points to.
public String type;
// URL for the resource that this Key points to, if one exists.
public String url;
*/
/**
* Public constructor
*/
public PartialDependenceKeyV3() {
name = "";
type = "";
url = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/PartialDependenceV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class PartialDependenceV3 extends SchemaV3 {
/**
* Model
*/
@SerializedName("model_id")
public ModelKeyV3 modelId;
/**
* Frame
*/
@SerializedName("frame_id")
public FrameKeyV3 frameId;
/**
* Row Index
*/
@SerializedName("row_index")
public long rowIndex;
/**
* Column(s)
*/
public String[] cols;
/**
* weight_column_index
*/
@SerializedName("weight_column_index")
public int weightColumnIndex;
/**
* add_missing_na
*/
@SerializedName("add_missing_na")
public boolean addMissingNa;
/**
* Number of bins
*/
public int nbins;
/**
* User define split points
*/
@SerializedName("user_splits")
public double[] userSplits;
/**
* Column(s) of user defined splits
*/
@SerializedName("user_cols")
public String[] userCols;
/**
* Number of user defined splits per column
*/
@SerializedName("num_user_splits")
public int[] numUserSplits;
/**
* Partial Dependence Data
*/
@SerializedName("partial_dependence_data")
public TwoDimTableV3[] partialDependenceData;
/**
* lists of column name pairs to plot 2D pdp for
*/
@SerializedName("col_pairs_2dpdp")
public String[][] colPairs2dpdp;
/**
* Key to store the destination
*/
@SerializedName("destination_key")
public PartialDependenceKeyV3 destinationKey;
/**
* Target classes for multinomial classification
*/
public String[] targets;
/**
* Public constructor
*/
public PartialDependenceV3() {
rowIndex = 0L;
weightColumnIndex = 0;
addMissingNa = false;
nbins = 0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/PersistS3CredentialsV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class PersistS3CredentialsV3 extends SchemaV3 {
/**
* S3 Secret Key ID
*/
@SerializedName("secret_key_id")
public String secretKeyId;
/**
* S3 Secret Key
*/
@SerializedName("secret_access_key")
public String secretAccessKey;
/**
* S3 Session token
*/
@SerializedName("session_token")
public String sessionToken;
/**
* Public constructor
*/
public PersistS3CredentialsV3() {
secretKeyId = "";
secretAccessKey = "";
sessionToken = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/PingV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class PingV3 extends RequestSchemaV3 {
/**
* cloud_uptime_millis
*/
@SerializedName("cloud_uptime_millis")
public long cloudUptimeMillis;
/**
* cloud_healthy
*/
@SerializedName("cloud_healthy")
public boolean cloudHealthy;
/**
* nodes
*/
public NodeMemoryInfoV3[] nodes;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public PingV3() {
cloudUptimeMillis = 0L;
cloudHealthy = false;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/PreprocessingStepDefinitionV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class PreprocessingStepDefinitionV99 {
/**
* A type representing the preprocessing step to be executed.
*/
public H2oautomlpreprocessingPreprocessingStepDefinitionType type;
/**
* Public constructor
*/
public PreprocessingStepDefinitionV99() {
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/ProfilerNodeEntryV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ProfilerNodeEntryV3 extends SchemaV3 {
/**
* Stack trace
*/
public String stacktrace;
/**
* Profile Count
*/
public int count;
/**
* Public constructor
*/
public ProfilerNodeEntryV3() {
stacktrace = "";
count = 0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/ProfilerNodeV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ProfilerNodeV3 extends SchemaV3 {
/**
* Node names
*/
@SerializedName("node_name")
public String nodeName;
/**
* Timestamp (millis since epoch)
*/
public long timestamp;
/**
* Profile entry list
*/
public ProfilerNodeEntryV3[] entries;
/**
* Public constructor
*/
public ProfilerNodeV3() {
nodeName = "";
timestamp = 0L;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/ProfilerV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ProfilerV3 extends RequestSchemaV3 {
/**
* Stack trace depth
*/
public int depth;
/**
*/
public ProfilerNodeV3[] nodes;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public ProfilerV3() {
depth = 10;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/QuantileModelCombineMethod.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum QuantileModelCombineMethod {
AVG,
HI,
INTERPOLATE,
LO,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/QuantileParametersV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class QuantileParametersV3 extends ModelParametersSchemaV3 {
/**
* Probabilities for quantiles
*/
public double[] probs;
/**
* How to combine quantiles for even sample sizes
*/
@SerializedName("combine_method")
public QuantileModelCombineMethod combineMethod;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Destination id for this model; auto-generated if not specified.
public ModelKeyV3 modelId;
// Id of the training data frame.
public FrameKeyV3 trainingFrame;
// Id of the validation data frame.
public FrameKeyV3 validationFrame;
// Number of folds for K-fold cross-validation (0 to disable or >= 2).
public int nfolds;
// Whether to keep the cross-validation models.
public boolean keepCrossValidationModels;
// Whether to keep the predictions of the cross-validation models.
public boolean keepCrossValidationPredictions;
// Whether to keep the cross-validation fold assignment.
public boolean keepCrossValidationFoldAssignment;
// Allow parallel training of cross-validation models
public boolean parallelizeCrossValidation;
// Distribution function
public GenmodelutilsDistributionFamily distribution;
// Tweedie power for Tweedie regression, must be between 1 and 2.
public double tweediePower;
// Desired quantile for Quantile regression, must be between 0 and 1.
public double quantileAlpha;
// Desired quantile for Huber/M-regression (threshold between quadratic and linear loss, must be between 0 and 1).
public double huberAlpha;
// Response variable column.
public ColSpecifierV3 responseColumn;
// Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
// dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights
// are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data frame.
// This is typically the number of times a row is repeated, but non-integer values are supported as well. During
// training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set weight = 0
// for a row, the returned prediction frame at that row is zero and this is incorrect. To get an accurate
// prediction, remove all rows with weight == 0.
public ColSpecifierV3 weightsColumn;
// Offset column. This will be added to the combination of columns before applying the link function.
public ColSpecifierV3 offsetColumn;
// Column with cross-validation fold index assignment per observation.
public ColSpecifierV3 foldColumn;
// Cross-validation fold assignment scheme, if fold_column is not specified. The 'Stratified' option will stratify
// the folds based on the response variable, for classification problems.
public ModelParametersFoldAssignmentScheme foldAssignment;
// Encoding scheme for categorical features
public ModelParametersCategoricalEncodingScheme categoricalEncoding;
// For every categorical feature, only use this many most frequent categorical levels for model training. Only used
// for categorical_encoding == EnumLimited.
public int maxCategoricalLevels;
// Names of columns to ignore for training.
public String[] ignoredColumns;
// Ignore constant columns.
public boolean ignoreConstCols;
// Whether to score during each iteration of model training.
public boolean scoreEachIteration;
// Model checkpoint to resume training with.
public ModelKeyV3 checkpoint;
// Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
// stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
public int stoppingRounds;
// Maximum allowed runtime in seconds for model training. Use 0 to disable.
public double maxRuntimeSecs;
// Metric to use for early stopping (AUTO: logloss for classification, deviance for regression and anomaly_score for
// Isolation Forest). Note that custom and custom_increasing can only be used in GBM and DRF with the Python client.
public ScoreKeeperStoppingMetric stoppingMetric;
// Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
public double stoppingTolerance;
// Gains/Lift table number of bins. 0 means disabled.. Default value -1 means automatic binning.
public int gainsliftBins;
// Reference to custom evaluation function, format: `language:keyName=funcName`
public String customMetricFunc;
// Reference to custom distribution, format: `language:keyName=funcName`
public String customDistributionFunc;
// Automatically export generated models to this directory.
public String exportCheckpointsDir;
// Set default multinomial AUC type.
public MultinomialAucType aucType;
*/
/**
* Public constructor
*/
public QuantileParametersV3() {
probs = new double[]{0.001, 0.01, 0.1, 0.25, 0.333, 0.5, 0.667, 0.75, 0.9, 0.99, 0.999};
combineMethod = QuantileModelCombineMethod.INTERPOLATE;
nfolds = 0;
keepCrossValidationModels = true;
keepCrossValidationPredictions = false;
keepCrossValidationFoldAssignment = false;
parallelizeCrossValidation = true;
distribution = GenmodelutilsDistributionFamily.AUTO;
tweediePower = 1.5;
quantileAlpha = 0.5;
huberAlpha = 0.9;
foldAssignment = ModelParametersFoldAssignmentScheme.AUTO;
categoricalEncoding = ModelParametersCategoricalEncodingScheme.AUTO;
maxCategoricalLevels = 10;
ignoreConstCols = false;
scoreEachIteration = false;
stoppingRounds = 0;
maxRuntimeSecs = 0.0;
stoppingMetric = ScoreKeeperStoppingMetric.AUTO;
stoppingTolerance = 0.001;
gainsliftBins = -1;
customMetricFunc = "";
customDistributionFunc = "";
exportCheckpointsDir = "";
aucType = MultinomialAucType.AUTO;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/QuantileV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class QuantileV3 extends ModelBuilderSchema<QuantileParametersV3> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Model builder parameters.
public QuantileParametersV3 parameters;
// The algo name for this ModelBuilder.
public String algo;
// The pretty algo name for this ModelBuilder (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// Model categories this ModelBuilder can build.
public ModelCategory[] canBuild;
// Indicator whether the model is supervised or not.
public boolean supervised;
// Should the builder always be visible, be marked as beta, or only visible if the user starts up with the
// experimental flag?
public ModelBuilderBuilderVisibility visibility;
// Job Key
public JobV3 job;
// Parameter validation messages
public ValidationMessageV3[] messages;
// Count of parameter validation errors
public int errorCount;
// HTTP status to return for this build.
public int __httpStatus;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public QuantileV3() {
algo = "";
algoFullName = "";
supervised = false;
errorCount = 0;
__httpStatus = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RandomDiscreteValueSearchCriteriaV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RandomDiscreteValueSearchCriteriaV99 extends HyperSpaceSearchCriteriaV99 {
/**
* Seed for random number generator; set to a value other than -1 for reproducibility.
*/
public long seed;
/**
* Maximum number of models to build (optional).
*/
@SerializedName("max_models")
public int maxModels;
/**
* Maximum time to spend building models (optional).
*/
@SerializedName("max_runtime_secs")
public double maxRuntimeSecs;
/**
* Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
* stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
*/
@SerializedName("stopping_rounds")
public int stoppingRounds;
/**
* Metric to use for early stopping (AUTO: logloss for classification, deviance for regression)
*/
@SerializedName("stopping_metric")
public ScoreKeeperStoppingMetric stoppingMetric;
/**
* Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
*/
@SerializedName("stopping_tolerance")
public double stoppingTolerance;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Hyperparameter space search strategy.
public GridHyperSpaceSearchCriteriaStrategy strategy;
*/
/**
* Public constructor
*/
public RandomDiscreteValueSearchCriteriaV99() {
seed = -1L;
maxModels = 0;
maxRuntimeSecs = 0.0;
stoppingRounds = 0;
stoppingMetric = ScoreKeeperStoppingMetric.AUTO;
stoppingTolerance = 0.001;
strategy = GridHyperSpaceSearchCriteriaStrategy.RandomDiscrete;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsExpressionV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsExpressionV3 extends SchemaV3 {
/**
* (Class) name of the language construct
*/
public String name;
/**
* Code fragment pattern.
*/
public String pattern;
/**
* Description of the functionality provided by this language construct.
*/
public String description;
/**
* Public constructor
*/
public RapidsExpressionV3() {
name = "";
pattern = "";
description = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsFrameV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsFrameV3 extends RapidsSchemaV3 {
/**
* Frame result
*/
public FrameKeyV3 key;
/**
* Rows in Frame result
*/
@SerializedName("num_rows")
public long numRows;
/**
* Columns in Frame result
*/
@SerializedName("num_cols")
public int numCols;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// A Rapids AstRoot expression
public String ast;
// Session key
public String sessionId;
// [DEPRECATED] Key name to assign Frame results
public String id;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsFrameV3() {
numRows = 0L;
numCols = 0;
ast = "";
sessionId = "";
id = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsFunctionV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsFunctionV3 extends RapidsSchemaV3 {
/**
* Function result
*/
public String funstr;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// A Rapids AstRoot expression
public String ast;
// Session key
public String sessionId;
// [DEPRECATED] Key name to assign Frame results
public String id;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsFunctionV3() {
funstr = "";
ast = "";
sessionId = "";
id = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsHelpV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsHelpV3 extends SchemaV3 {
/**
* Description of the rapids language.
*/
public RapidsExpressionV3[] expressions;
/**
* Public constructor
*/
public RapidsHelpV3() {
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsMapFrameV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsMapFrameV3 extends RapidsSchemaV3 {
/**
* Frames
*/
public RapidsFrameV3[] frames;
/**
* Keys of the map
*/
@SerializedName("map_keys")
public RapidsStringsV3 mapKeys;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// A Rapids AstRoot expression
public String ast;
// Session key
public String sessionId;
// [DEPRECATED] Key name to assign Frame results
public String id;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsMapFrameV3() {
ast = "";
sessionId = "";
id = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsNumberV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsNumberV3 extends RapidsSchemaV3 {
/**
* Number result
*/
public double scalar;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// A Rapids AstRoot expression
public String ast;
// Session key
public String sessionId;
// [DEPRECATED] Key name to assign Frame results
public String id;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsNumberV3() {
scalar = 0.0;
ast = "";
sessionId = "";
id = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsNumbersV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsNumbersV3 extends RapidsSchemaV3 {
/**
* Number array result
*/
public double[] scalar;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// A Rapids AstRoot expression
public String ast;
// Session key
public String sessionId;
// [DEPRECATED] Key name to assign Frame results
public String id;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsNumbersV3() {
ast = "";
sessionId = "";
id = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsSchemaV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsSchemaV3 extends RequestSchemaV3 {
/**
* A Rapids AstRoot expression
*/
public String ast;
/**
* Session key
*/
@SerializedName("session_id")
public String sessionId;
/**
* [DEPRECATED] Key name to assign Frame results
*/
public String id;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsSchemaV3() {
ast = "";
sessionId = "";
id = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsStringV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsStringV3 extends RapidsSchemaV3 {
/**
* String result
*/
public String string;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// A Rapids AstRoot expression
public String ast;
// Session key
public String sessionId;
// [DEPRECATED] Key name to assign Frame results
public String id;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsStringV3() {
string = "";
ast = "";
sessionId = "";
id = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsStringsV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsStringsV3 extends RapidsSchemaV3 {
/**
* String array result
*/
public String[] string;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// A Rapids AstRoot expression
public String ast;
// Session key
public String sessionId;
// [DEPRECATED] Key name to assign Frame results
public String id;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsStringsV3() {
ast = "";
sessionId = "";
id = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RapidsV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RapidsV99 extends RequestSchemaV3 {
/**
* An Abstract Syntax Tree.
*/
public String ast;
/**
* Parsing error, if any
*/
public String error;
/**
* Scalar result
*/
public double scalar;
/**
* Function result
*/
public String funstr;
/**
* String result
*/
public String string;
/**
* Result key
*/
public FrameKeyV3 key;
/**
* Rows in Frame result
*/
@SerializedName("num_rows")
public long numRows;
/**
* Columns in Frame result
*/
@SerializedName("num_cols")
public int numCols;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RapidsV99() {
ast = "";
error = "";
scalar = 0.0;
funstr = "";
string = "";
numRows = 0L;
numCols = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RemoveAllV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RemoveAllV3 extends RequestSchemaV3 {
/**
* Keys of the models to retain
*/
@SerializedName("retained_keys")
public KeyV3[] retainedKeys;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RemoveAllV3() {
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RemoveV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RemoveV3 extends RequestSchemaV3 {
/**
* Object to be removed.
*/
public KeyV3 key;
/**
* If true, removal operation will cascade down the object tree.
*/
public boolean cascade;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RemoveV3() {
cascade = false;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RequestSchemaV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RequestSchemaV3 extends SchemaV3 {
/**
* Comma-separated list of JSON field paths to exclude from the result, used like:
* "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
*/
@SerializedName("_exclude_fields")
public String _excludeFields;
/**
* Public constructor
*/
public RequestSchemaV3() {
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/ResumeV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ResumeV3 extends SchemaV3 {
/**
* Full path to the directory with recovery data
*/
@SerializedName("recovery_dir")
public String recoveryDir;
/**
* Public constructor
*/
public ResumeV3() {
recoveryDir = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RouteV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RouteV3 extends SchemaV3 {
/**
*/
@SerializedName("http_method")
public String httpMethod;
/**
*/
@SerializedName("url_pattern")
public String urlPattern;
/**
*/
public String summary;
/**
*/
@SerializedName("api_name")
public String apiName;
/**
*/
@SerializedName("handler_class")
public String handlerClass;
/**
*/
@SerializedName("handler_method")
public String handlerMethod;
/**
*/
@SerializedName("input_schema")
public String inputSchema;
/**
*/
@SerializedName("output_schema")
public String outputSchema;
/**
*/
@SerializedName("path_params")
public String[] pathParams;
/**
*/
public String markdown;
/**
* Public constructor
*/
public RouteV3() {
httpMethod = "";
urlPattern = "";
summary = "";
apiName = "";
handlerClass = "";
handlerMethod = "";
inputSchema = "";
outputSchema = "";
markdown = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RuleFitModelAlgorithm.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum RuleFitModelAlgorithm {
AUTO,
DRF,
GBM,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RuleFitModelModelType.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum RuleFitModelModelType {
LINEAR,
RULES,
RULES_AND_LINEAR,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RuleFitModelOutputV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RuleFitModelOutputV3 extends ModelOutputSchemaV3 {
/**
* The estimated coefficients without language representations for each of the significant baselearners.
*/
@SerializedName("rule_importance")
public TwoDimTableV3 ruleImportance;
/**
* Intercept.
*/
public double[] intercept;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Column names
public String[] names;
// Original column names
public String[] originalNames;
// Column types
public String[] columnTypes;
// Domains for categorical columns
public String[][] domains;
// Cross-validation models (model ids)
public ModelKeyV3[] crossValidationModels;
// Cross-validation predictions, one per cv model (deprecated, use cross_validation_holdout_predictions_frame_id
// instead)
public FrameKeyV3[] crossValidationPredictions;
// Cross-validation holdout predictions (full out-of-sample predictions on training data)
public FrameKeyV3 crossValidationHoldoutPredictionsFrameId;
// Cross-validation fold assignment (each row is assigned to one holdout fold)
public FrameKeyV3 crossValidationFoldAssignmentFrameId;
// Category of the model (e.g., Binomial)
public ModelCategory modelCategory;
// Model summary
public TwoDimTableV3 modelSummary;
// Scoring history
public TwoDimTableV3 scoringHistory;
// Cross-Validation scoring history
public TwoDimTableV3[] cvScoringHistory;
// Model reproducibility information
public TwoDimTableV3[] reproducibilityInformationTable;
// Training data model metrics
public ModelMetricsBaseV3 trainingMetrics;
// Validation data model metrics
public ModelMetricsBaseV3 validationMetrics;
// Cross-validation model metrics
public ModelMetricsBaseV3 crossValidationMetrics;
// Cross-validation model metrics summary
public TwoDimTableV3 crossValidationMetricsSummary;
// Job status
public String status;
// Start time in milliseconds
public long startTime;
// End time in milliseconds
public long endTime;
// Runtime in milliseconds
public long runTime;
// Default threshold used for predictions
public double defaultThreshold;
// Help information for output fields
public Map<String,String> help;
*/
/**
* Public constructor
*/
public RuleFitModelOutputV3() {
status = "";
startTime = 0L;
endTime = 0L;
runTime = 0L;
defaultThreshold = 0.0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RuleFitModelV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RuleFitModelV3 extends ModelSchemaV3<RuleFitParametersV3, RuleFitModelOutputV3> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// The build parameters for the model (e.g. K for KMeans).
public RuleFitParametersV3 parameters;
// The build output for the model (e.g. the cluster centers for KMeans).
public RuleFitModelOutputV3 output;
// Compatible frames, if requested
public String[] compatibleFrames;
// Checksum for all the things that go into building the Model.
public long checksum;
// Model key
public ModelKeyV3 modelId;
// The algo name for this Model.
public String algo;
// The pretty algo name for this Model (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// The response column name for this Model (if applicable). Is null otherwise.
public String responseColumnName;
// The treatment column name for this Model (if applicable). Is null otherwise.
public String treatmentColumnName;
// The Model's training frame key
public FrameKeyV3 dataFrame;
// Timestamp for when this model was completed
public long timestamp;
// Indicator, whether export to POJO is available
public boolean havePojo;
// Indicator, whether export to MOJO is available
public boolean haveMojo;
*/
/**
* Public constructor
*/
public RuleFitModelV3() {
checksum = 0L;
algo = "";
algoFullName = "";
responseColumnName = "";
treatmentColumnName = "";
timestamp = 0L;
havePojo = false;
haveMojo = false;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RuleFitParametersV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RuleFitParametersV3 extends ModelParametersSchemaV3 {
/**
* Seed for pseudo random number generator (if applicable).
*/
public long seed;
/**
* The algorithm to use to generate rules.
*/
public RuleFitModelAlgorithm algorithm;
/**
* Minimum length of rules. Defaults to 3.
*/
@SerializedName("min_rule_length")
public int minRuleLength;
/**
* Maximum length of rules. Defaults to 3.
*/
@SerializedName("max_rule_length")
public int maxRuleLength;
/**
* The maximum number of rules to return. defaults to -1 which means the number of rules is selected
* by diminishing returns in model deviance.
*/
@SerializedName("max_num_rules")
public int maxNumRules;
/**
* Specifies type of base learners in the ensemble.
*/
@SerializedName("model_type")
public RuleFitModelModelType modelType;
/**
* Specifies the number of trees to build in the tree model. Defaults to 50.
*/
@SerializedName("rule_generation_ntrees")
public int ruleGenerationNtrees;
/**
* Whether to remove rules which are identical to an earlier rule. Defaults to true.
*/
@SerializedName("remove_duplicates")
public boolean removeDuplicates;
/**
* Lambda for LASSO regressor.
*/
public double[] lambda;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Destination id for this model; auto-generated if not specified.
public ModelKeyV3 modelId;
// Id of the training data frame.
public FrameKeyV3 trainingFrame;
// Id of the validation data frame.
public FrameKeyV3 validationFrame;
// Number of folds for K-fold cross-validation (0 to disable or >= 2).
public int nfolds;
// Whether to keep the cross-validation models.
public boolean keepCrossValidationModels;
// Whether to keep the predictions of the cross-validation models.
public boolean keepCrossValidationPredictions;
// Whether to keep the cross-validation fold assignment.
public boolean keepCrossValidationFoldAssignment;
// Allow parallel training of cross-validation models
public boolean parallelizeCrossValidation;
// Distribution function
public GenmodelutilsDistributionFamily distribution;
// Tweedie power for Tweedie regression, must be between 1 and 2.
public double tweediePower;
// Desired quantile for Quantile regression, must be between 0 and 1.
public double quantileAlpha;
// Desired quantile for Huber/M-regression (threshold between quadratic and linear loss, must be between 0 and 1).
public double huberAlpha;
// Response variable column.
public ColSpecifierV3 responseColumn;
// Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
// dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights
// are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data frame.
// This is typically the number of times a row is repeated, but non-integer values are supported as well. During
// training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set weight = 0
// for a row, the returned prediction frame at that row is zero and this is incorrect. To get an accurate
// prediction, remove all rows with weight == 0.
public ColSpecifierV3 weightsColumn;
// Offset column. This will be added to the combination of columns before applying the link function.
public ColSpecifierV3 offsetColumn;
// Column with cross-validation fold index assignment per observation.
public ColSpecifierV3 foldColumn;
// Cross-validation fold assignment scheme, if fold_column is not specified. The 'Stratified' option will stratify
// the folds based on the response variable, for classification problems.
public ModelParametersFoldAssignmentScheme foldAssignment;
// Encoding scheme for categorical features
public ModelParametersCategoricalEncodingScheme categoricalEncoding;
// For every categorical feature, only use this many most frequent categorical levels for model training. Only used
// for categorical_encoding == EnumLimited.
public int maxCategoricalLevels;
// Names of columns to ignore for training.
public String[] ignoredColumns;
// Ignore constant columns.
public boolean ignoreConstCols;
// Whether to score during each iteration of model training.
public boolean scoreEachIteration;
// Model checkpoint to resume training with.
public ModelKeyV3 checkpoint;
// Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
// stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
public int stoppingRounds;
// Maximum allowed runtime in seconds for model training. Use 0 to disable.
public double maxRuntimeSecs;
// Metric to use for early stopping (AUTO: logloss for classification, deviance for regression and anomaly_score for
// Isolation Forest). Note that custom and custom_increasing can only be used in GBM and DRF with the Python client.
public ScoreKeeperStoppingMetric stoppingMetric;
// Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
public double stoppingTolerance;
// Gains/Lift table number of bins. 0 means disabled.. Default value -1 means automatic binning.
public int gainsliftBins;
// Reference to custom evaluation function, format: `language:keyName=funcName`
public String customMetricFunc;
// Reference to custom distribution, format: `language:keyName=funcName`
public String customDistributionFunc;
// Automatically export generated models to this directory.
public String exportCheckpointsDir;
// Set default multinomial AUC type.
public MultinomialAucType aucType;
*/
/**
* Public constructor
*/
public RuleFitParametersV3() {
seed = -1L;
algorithm = RuleFitModelAlgorithm.AUTO;
minRuleLength = 3;
maxRuleLength = 3;
maxNumRules = -1;
modelType = RuleFitModelModelType.RULES_AND_LINEAR;
ruleGenerationNtrees = 50;
removeDuplicates = true;
nfolds = 0;
keepCrossValidationModels = true;
keepCrossValidationPredictions = false;
keepCrossValidationFoldAssignment = false;
parallelizeCrossValidation = true;
distribution = GenmodelutilsDistributionFamily.AUTO;
tweediePower = 1.5;
quantileAlpha = 0.5;
huberAlpha = 0.9;
foldAssignment = ModelParametersFoldAssignmentScheme.AUTO;
categoricalEncoding = ModelParametersCategoricalEncodingScheme.AUTO;
maxCategoricalLevels = 10;
ignoreConstCols = true;
scoreEachIteration = false;
stoppingRounds = 0;
maxRuntimeSecs = 0.0;
stoppingMetric = ScoreKeeperStoppingMetric.AUTO;
stoppingTolerance = 0.001;
gainsliftBins = -1;
customMetricFunc = "";
customDistributionFunc = "";
exportCheckpointsDir = "";
aucType = MultinomialAucType.AUTO;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/RuleFitV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class RuleFitV3 extends ModelBuilderSchema<RuleFitParametersV3> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Model builder parameters.
public RuleFitParametersV3 parameters;
// The algo name for this ModelBuilder.
public String algo;
// The pretty algo name for this ModelBuilder (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// Model categories this ModelBuilder can build.
public ModelCategory[] canBuild;
// Indicator whether the model is supervised or not.
public boolean supervised;
// Should the builder always be visible, be marked as beta, or only visible if the user starts up with the
// experimental flag?
public ModelBuilderBuilderVisibility visibility;
// Job Key
public JobV3 job;
// Parameter validation messages
public ValidationMessageV3[] messages;
// Count of parameter validation errors
public int errorCount;
// HTTP status to return for this build.
public int __httpStatus;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public RuleFitV3() {
algo = "";
algoFullName = "";
supervised = false;
errorCount = 0;
__httpStatus = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SVDMethod.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum SVDMethod {
GramSVD,
Power,
Randomized,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SVDModelOutputV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SVDModelOutputV99 extends ModelOutputSchemaV3 {
/**
* Frame key of right singular vectors
*/
@SerializedName("v_key")
public FrameKeyV3 vKey;
/**
* Singular values
*/
public double[] d;
/**
* Frame key of left singular vectors
*/
@SerializedName("u_key")
public FrameKeyV3 uKey;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Column names
public String[] names;
// Original column names
public String[] originalNames;
// Column types
public String[] columnTypes;
// Domains for categorical columns
public String[][] domains;
// Cross-validation models (model ids)
public ModelKeyV3[] crossValidationModels;
// Cross-validation predictions, one per cv model (deprecated, use cross_validation_holdout_predictions_frame_id
// instead)
public FrameKeyV3[] crossValidationPredictions;
// Cross-validation holdout predictions (full out-of-sample predictions on training data)
public FrameKeyV3 crossValidationHoldoutPredictionsFrameId;
// Cross-validation fold assignment (each row is assigned to one holdout fold)
public FrameKeyV3 crossValidationFoldAssignmentFrameId;
// Category of the model (e.g., Binomial)
public ModelCategory modelCategory;
// Model summary
public TwoDimTableV3 modelSummary;
// Scoring history
public TwoDimTableV3 scoringHistory;
// Cross-Validation scoring history
public TwoDimTableV3[] cvScoringHistory;
// Model reproducibility information
public TwoDimTableV3[] reproducibilityInformationTable;
// Training data model metrics
public ModelMetricsBaseV3 trainingMetrics;
// Validation data model metrics
public ModelMetricsBaseV3 validationMetrics;
// Cross-validation model metrics
public ModelMetricsBaseV3 crossValidationMetrics;
// Cross-validation model metrics summary
public TwoDimTableV3 crossValidationMetricsSummary;
// Job status
public String status;
// Start time in milliseconds
public long startTime;
// End time in milliseconds
public long endTime;
// Runtime in milliseconds
public long runTime;
// Default threshold used for predictions
public double defaultThreshold;
// Help information for output fields
public Map<String,String> help;
*/
/**
* Public constructor
*/
public SVDModelOutputV99() {
status = "";
startTime = 0L;
endTime = 0L;
runTime = 0L;
defaultThreshold = 0.0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SVDModelV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SVDModelV99 extends ModelSchemaV3<SVDParametersV99, SVDModelOutputV99> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// The build parameters for the model (e.g. K for KMeans).
public SVDParametersV99 parameters;
// The build output for the model (e.g. the cluster centers for KMeans).
public SVDModelOutputV99 output;
// Compatible frames, if requested
public String[] compatibleFrames;
// Checksum for all the things that go into building the Model.
public long checksum;
// Model key
public ModelKeyV3 modelId;
// The algo name for this Model.
public String algo;
// The pretty algo name for this Model (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// The response column name for this Model (if applicable). Is null otherwise.
public String responseColumnName;
// The treatment column name for this Model (if applicable). Is null otherwise.
public String treatmentColumnName;
// The Model's training frame key
public FrameKeyV3 dataFrame;
// Timestamp for when this model was completed
public long timestamp;
// Indicator, whether export to POJO is available
public boolean havePojo;
// Indicator, whether export to MOJO is available
public boolean haveMojo;
*/
/**
* Public constructor
*/
public SVDModelV99() {
checksum = 0L;
algo = "";
algoFullName = "";
responseColumnName = "";
treatmentColumnName = "";
timestamp = 0L;
havePojo = false;
haveMojo = false;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SVDParametersV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SVDParametersV99 extends ModelParametersSchemaV3 {
/**
* Transformation of training data
*/
public DataInfoTransformType transform;
/**
* Method for computing SVD (Caution: Randomized is currently experimental and unstable)
*/
@SerializedName("svd_method")
public SVDMethod svdMethod;
/**
* Number of right singular vectors
*/
public int nv;
/**
* Maximum iterations
*/
@SerializedName("max_iterations")
public int maxIterations;
/**
* RNG seed for k-means++ initialization
*/
public long seed;
/**
* Save left singular vectors?
*/
@SerializedName("keep_u")
public boolean keepU;
/**
* Frame key to save left singular vectors
*/
@SerializedName("u_name")
public String uName;
/**
* Whether first factor level is included in each categorical expansion
*/
@SerializedName("use_all_factor_levels")
public boolean useAllFactorLevels;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Destination id for this model; auto-generated if not specified.
public ModelKeyV3 modelId;
// Id of the training data frame.
public FrameKeyV3 trainingFrame;
// Id of the validation data frame.
public FrameKeyV3 validationFrame;
// Number of folds for K-fold cross-validation (0 to disable or >= 2).
public int nfolds;
// Whether to keep the cross-validation models.
public boolean keepCrossValidationModels;
// Whether to keep the predictions of the cross-validation models.
public boolean keepCrossValidationPredictions;
// Whether to keep the cross-validation fold assignment.
public boolean keepCrossValidationFoldAssignment;
// Allow parallel training of cross-validation models
public boolean parallelizeCrossValidation;
// Distribution function
public GenmodelutilsDistributionFamily distribution;
// Tweedie power for Tweedie regression, must be between 1 and 2.
public double tweediePower;
// Desired quantile for Quantile regression, must be between 0 and 1.
public double quantileAlpha;
// Desired quantile for Huber/M-regression (threshold between quadratic and linear loss, must be between 0 and 1).
public double huberAlpha;
// Response variable column.
public ColSpecifierV3 responseColumn;
// Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
// dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights
// are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data frame.
// This is typically the number of times a row is repeated, but non-integer values are supported as well. During
// training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set weight = 0
// for a row, the returned prediction frame at that row is zero and this is incorrect. To get an accurate
// prediction, remove all rows with weight == 0.
public ColSpecifierV3 weightsColumn;
// Offset column. This will be added to the combination of columns before applying the link function.
public ColSpecifierV3 offsetColumn;
// Column with cross-validation fold index assignment per observation.
public ColSpecifierV3 foldColumn;
// Cross-validation fold assignment scheme, if fold_column is not specified. The 'Stratified' option will stratify
// the folds based on the response variable, for classification problems.
public ModelParametersFoldAssignmentScheme foldAssignment;
// Encoding scheme for categorical features
public ModelParametersCategoricalEncodingScheme categoricalEncoding;
// For every categorical feature, only use this many most frequent categorical levels for model training. Only used
// for categorical_encoding == EnumLimited.
public int maxCategoricalLevels;
// Names of columns to ignore for training.
public String[] ignoredColumns;
// Ignore constant columns.
public boolean ignoreConstCols;
// Whether to score during each iteration of model training.
public boolean scoreEachIteration;
// Model checkpoint to resume training with.
public ModelKeyV3 checkpoint;
// Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
// stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
public int stoppingRounds;
// Maximum allowed runtime in seconds for model training. Use 0 to disable.
public double maxRuntimeSecs;
// Metric to use for early stopping (AUTO: logloss for classification, deviance for regression and anomaly_score for
// Isolation Forest). Note that custom and custom_increasing can only be used in GBM and DRF with the Python client.
public ScoreKeeperStoppingMetric stoppingMetric;
// Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
public double stoppingTolerance;
// Gains/Lift table number of bins. 0 means disabled.. Default value -1 means automatic binning.
public int gainsliftBins;
// Reference to custom evaluation function, format: `language:keyName=funcName`
public String customMetricFunc;
// Reference to custom distribution, format: `language:keyName=funcName`
public String customDistributionFunc;
// Automatically export generated models to this directory.
public String exportCheckpointsDir;
// Set default multinomial AUC type.
public MultinomialAucType aucType;
*/
/**
* Public constructor
*/
public SVDParametersV99() {
transform = DataInfoTransformType.NONE;
svdMethod = SVDMethod.GramSVD;
nv = 1;
maxIterations = 1000;
seed = -1L;
keepU = true;
uName = "";
useAllFactorLevels = true;
nfolds = 0;
keepCrossValidationModels = true;
keepCrossValidationPredictions = false;
keepCrossValidationFoldAssignment = false;
parallelizeCrossValidation = true;
distribution = GenmodelutilsDistributionFamily.AUTO;
tweediePower = 1.5;
quantileAlpha = 0.5;
huberAlpha = 0.9;
foldAssignment = ModelParametersFoldAssignmentScheme.AUTO;
categoricalEncoding = ModelParametersCategoricalEncodingScheme.AUTO;
maxCategoricalLevels = 10;
ignoreConstCols = true;
scoreEachIteration = false;
stoppingRounds = 0;
maxRuntimeSecs = 0.0;
stoppingMetric = ScoreKeeperStoppingMetric.AUTO;
stoppingTolerance = 0.001;
gainsliftBins = -1;
customMetricFunc = "";
customDistributionFunc = "";
exportCheckpointsDir = "";
aucType = MultinomialAucType.AUTO;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SVDV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SVDV99 extends ModelBuilderSchema<SVDParametersV99> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Model builder parameters.
public SVDParametersV99 parameters;
// The algo name for this ModelBuilder.
public String algo;
// The pretty algo name for this ModelBuilder (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// Model categories this ModelBuilder can build.
public ModelCategory[] canBuild;
// Indicator whether the model is supervised or not.
public boolean supervised;
// Should the builder always be visible, be marked as beta, or only visible if the user starts up with the
// experimental flag?
public ModelBuilderBuilderVisibility visibility;
// Job Key
public JobV3 job;
// Parameter validation messages
public ValidationMessageV3[] messages;
// Count of parameter validation errors
public int errorCount;
// HTTP status to return for this build.
public int __httpStatus;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public SVDV99() {
algo = "";
algoFullName = "";
supervised = false;
errorCount = 0;
__httpStatus = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SaveToHiveTableV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SaveToHiveTableV3 extends RequestSchemaV3 {
/**
* H2O Frame ID
*/
@SerializedName("frame_id")
public FrameKeyV3 frameId;
/**
* HIVE JDBC URL
*/
@SerializedName("jdbc_url")
public String jdbcUrl;
/**
* Name of table to save data to.
*/
@SerializedName("table_name")
public String tableName;
/**
* HDFS Path to where the table should be stored.
*/
@SerializedName("table_path")
public String tablePath;
/**
* Storage format of the created table.
*/
public ApiSaveToHiveTableHandlerHiveFrameSaverFormat format;
/**
* HDFS Path where to store temporary data.
*/
@SerializedName("tmp_path")
public String tmpPath;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public SaveToHiveTableV3() {
jdbcUrl = "";
tableName = "";
tablePath = "";
tmpPath = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SchemaMetadataV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SchemaMetadataV3 extends SchemaV3 {
/**
* Version number of the Schema.
*/
public int version;
/**
* Simple name of the Schema. NOTE: the schema_names form a single namespace.
*/
public String name;
/**
* [DEPRECATED] This field is always the same as name.
*/
public String label;
/**
* Simple name of the superclass of the Schema. NOTE: the schema_names form a single namespace.
*/
public String superclass;
/**
* Simple name of H2O type that this Schema represents. Must not be changed after creation (treat as final).
*/
public String type;
/**
* All the public fields of the schema
*/
public FieldMetadataV3[] fields;
/**
* Documentation for the schema in Markdown format with GitHub extensions
*/
public String markdown;
/**
* Public constructor
*/
public SchemaMetadataV3() {
version = 0;
name = "";
label = "";
superclass = "";
type = "";
fields = new FieldMetadataV3[]{};
markdown = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SchemaV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SchemaV3 {
/**
* Public constructor
*/
public SchemaV3() {
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/ScoreKeeperStoppingMetric.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum ScoreKeeperStoppingMetric {
ATC,
ATE,
ATT,
AUC,
AUCPR,
AUTO,
AUUC,
MAE,
MSE,
RMSE,
RMSLE,
anomaly_score,
custom,
custom_increasing,
deviance,
lift_top_group,
logloss,
mean_per_class_error,
misclassification,
qini,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SegmentModelsKeyV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SegmentModelsKeyV3 extends KeyV3 {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Name (string representation) for this Key.
public String name;
// Name (string representation) for the type of Keyed this Key points to.
public String type;
// URL for the resource that this Key points to, if one exists.
public String url;
*/
/**
* Public constructor
*/
public SegmentModelsKeyV3() {
name = "";
type = "";
url = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SegmentModelsParametersV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SegmentModelsParametersV3 extends SchemaV3 {
/**
* Uniquely identifies the collection of the segment models
*/
@SerializedName("segment_models_id")
public SegmentModelsKeyV3 segmentModelsId;
/**
* Enumeration of all segments for which to build models for
*/
public FrameKeyV3 segments;
/**
* List of columns to segment-by, models will be built for all segments in the data
*/
@SerializedName("segment_columns")
public String[] segmentColumns;
/**
* Level of parallelism of bulk model building, it is the maximum number of models each H2O node will be building in
* parallel
*/
public int parallelism;
/**
* Public constructor
*/
public SegmentModelsParametersV3() {
parallelism = 1;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SegmentModelsV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SegmentModelsV3 extends SchemaV3 {
/**
* Segment Models id
*/
@SerializedName("segment_models_id")
public SegmentModelsKeyV3 segmentModelsId;
/**
* Public constructor
*/
public SegmentModelsV3() {
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SequentialSearchCriteriaV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SequentialSearchCriteriaV99 extends HyperSpaceSearchCriteriaV99 {
/**
* Maximum number of models to build (optional).
*/
@SerializedName("max_models")
public int maxModels;
/**
* Maximum time to spend building models (optional).
*/
@SerializedName("max_runtime_secs")
public double maxRuntimeSecs;
/**
* Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
* stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
*/
@SerializedName("stopping_rounds")
public int stoppingRounds;
/**
* Metric to use for early stopping (AUTO: logloss for classification, deviance for regression)
*/
@SerializedName("stopping_metric")
public ScoreKeeperStoppingMetric stoppingMetric;
/**
* Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
*/
@SerializedName("stopping_tolerance")
public double stoppingTolerance;
/**
* Use early stopping
*/
@SerializedName("early_stopping")
public boolean earlyStopping;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Hyperparameter space search strategy.
public GridHyperSpaceSearchCriteriaStrategy strategy;
*/
/**
* Public constructor
*/
public SequentialSearchCriteriaV99() {
maxModels = 0;
maxRuntimeSecs = 0.0;
stoppingRounds = 0;
stoppingMetric = ScoreKeeperStoppingMetric.AUTO;
stoppingTolerance = 0.001;
earlyStopping = true;
strategy = GridHyperSpaceSearchCriteriaStrategy.Sequential;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SessionIdV4.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SessionIdV4 extends OutputSchemaV4 {
/**
* Session ID
*/
@SerializedName("session_key")
public String sessionKey;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Url describing the schema of the current object.
public String __schema;
*/
/**
* Public constructor
*/
public SessionIdV4() {
sessionKey = "";
__schema = "/4/schemas/SessionIdV4";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SessionPropertyV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SessionPropertyV3 extends RequestSchemaV3 {
/**
* Session ID
*/
@SerializedName("session_key")
public String sessionKey;
/**
* Property Key
*/
public String key;
/**
* Property Value
*/
public String value;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public SessionPropertyV3() {
sessionKey = "";
key = "";
value = "";
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SharedTreeModelOutputV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SharedTreeModelOutputV3 extends ModelOutputSchemaV3 {
/**
* Variable Importances
*/
@SerializedName("variable_importances")
public TwoDimTableV3 variableImportances;
/**
* The Intercept term, the initial model function value to which trees make adjustments
*/
@SerializedName("init_f")
public double initF;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Column names
public String[] names;
// Original column names
public String[] originalNames;
// Column types
public String[] columnTypes;
// Domains for categorical columns
public String[][] domains;
// Cross-validation models (model ids)
public ModelKeyV3[] crossValidationModels;
// Cross-validation predictions, one per cv model (deprecated, use cross_validation_holdout_predictions_frame_id
// instead)
public FrameKeyV3[] crossValidationPredictions;
// Cross-validation holdout predictions (full out-of-sample predictions on training data)
public FrameKeyV3 crossValidationHoldoutPredictionsFrameId;
// Cross-validation fold assignment (each row is assigned to one holdout fold)
public FrameKeyV3 crossValidationFoldAssignmentFrameId;
// Category of the model (e.g., Binomial)
public ModelCategory modelCategory;
// Model summary
public TwoDimTableV3 modelSummary;
// Scoring history
public TwoDimTableV3 scoringHistory;
// Cross-Validation scoring history
public TwoDimTableV3[] cvScoringHistory;
// Model reproducibility information
public TwoDimTableV3[] reproducibilityInformationTable;
// Training data model metrics
public ModelMetricsBaseV3 trainingMetrics;
// Validation data model metrics
public ModelMetricsBaseV3 validationMetrics;
// Cross-validation model metrics
public ModelMetricsBaseV3 crossValidationMetrics;
// Cross-validation model metrics summary
public TwoDimTableV3 crossValidationMetricsSummary;
// Job status
public String status;
// Start time in milliseconds
public long startTime;
// End time in milliseconds
public long endTime;
// Runtime in milliseconds
public long runTime;
// Default threshold used for predictions
public double defaultThreshold;
// Help information for output fields
public Map<String,String> help;
*/
/**
* Public constructor
*/
public SharedTreeModelOutputV3() {
initF = 0.0;
status = "";
startTime = 0L;
endTime = 0L;
runTime = 0L;
defaultThreshold = 0.0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SharedTreeModelV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SharedTreeModelV3<P extends ModelParametersSchemaV3, O extends ModelOutputSchemaV3> extends ModelSchemaV3<P, O> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// The build parameters for the model (e.g. K for KMeans).
public P parameters;
// The build output for the model (e.g. the cluster centers for KMeans).
public O output;
// Compatible frames, if requested
public String[] compatibleFrames;
// Checksum for all the things that go into building the Model.
public long checksum;
// Model key
public ModelKeyV3 modelId;
// The algo name for this Model.
public String algo;
// The pretty algo name for this Model (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// The response column name for this Model (if applicable). Is null otherwise.
public String responseColumnName;
// The treatment column name for this Model (if applicable). Is null otherwise.
public String treatmentColumnName;
// The Model's training frame key
public FrameKeyV3 dataFrame;
// Timestamp for when this model was completed
public long timestamp;
// Indicator, whether export to POJO is available
public boolean havePojo;
// Indicator, whether export to MOJO is available
public boolean haveMojo;
*/
/**
* Public constructor
*/
public SharedTreeModelV3() {
checksum = 0L;
algo = "";
algoFullName = "";
responseColumnName = "";
treatmentColumnName = "";
timestamp = 0L;
havePojo = false;
haveMojo = false;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SharedTreeParametersV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SharedTreeParametersV3 extends ModelParametersSchemaV3 {
/**
* Balance training data class counts via over/under-sampling (for imbalanced data).
*/
@SerializedName("balance_classes")
public boolean balanceClasses;
/**
* Desired over/under-sampling ratios per class (in lexicographic order). If not specified, sampling factors will be
* automatically computed to obtain class balance during training. Requires balance_classes.
*/
@SerializedName("class_sampling_factors")
public float[] classSamplingFactors;
/**
* Maximum relative size of the training data after balancing class counts (can be less than 1.0). Requires
* balance_classes.
*/
@SerializedName("max_after_balance_size")
public float maxAfterBalanceSize;
/**
* [Deprecated] Maximum size (# classes) for confusion matrices to be printed in the Logs
*/
@SerializedName("max_confusion_matrix_size")
public int maxConfusionMatrixSize;
/**
* Number of trees.
*/
public int ntrees;
/**
* Maximum tree depth (0 for unlimited).
*/
@SerializedName("max_depth")
public int maxDepth;
/**
* Fewest allowed (weighted) observations in a leaf.
*/
@SerializedName("min_rows")
public double minRows;
/**
* For numerical columns (real/int), build a histogram of (at least) this many bins, then split at the best point
*/
public int nbins;
/**
* For numerical columns (real/int), build a histogram of (at most) this many bins at the root level, then decrease
* by factor of two per level
*/
@SerializedName("nbins_top_level")
public int nbinsTopLevel;
/**
* For categorical columns (factors), build a histogram of this many bins, then split at the best point. Higher
* values can lead to more overfitting.
*/
@SerializedName("nbins_cats")
public int nbinsCats;
/**
* r2_stopping is no longer supported and will be ignored if set - please use stopping_rounds, stopping_metric and
* stopping_tolerance instead. Previous version of H2O would stop making trees when the R^2 metric equals or exceeds
* this
*/
@SerializedName("r2_stopping")
public double r2Stopping;
/**
* Seed for pseudo random number generator (if applicable)
*/
public long seed;
/**
* Run on one node only; no network overhead but fewer cpus used. Suitable for small datasets.
*/
@SerializedName("build_tree_one_node")
public boolean buildTreeOneNode;
/**
* A list of row sample rates per class (relative fraction for each class, from 0.0 to 1.0), for each tree
*/
@SerializedName("sample_rate_per_class")
public double[] sampleRatePerClass;
/**
* Column sample rate per tree (from 0.0 to 1.0)
*/
@SerializedName("col_sample_rate_per_tree")
public double colSampleRatePerTree;
/**
* Relative change of the column sampling rate for every level (must be > 0.0 and <= 2.0)
*/
@SerializedName("col_sample_rate_change_per_level")
public double colSampleRateChangePerLevel;
/**
* Score the model after every so many trees. Disabled if set to 0.
*/
@SerializedName("score_tree_interval")
public int scoreTreeInterval;
/**
* Minimum relative improvement in squared error reduction for a split to happen
*/
@SerializedName("min_split_improvement")
public double minSplitImprovement;
/**
* What type of histogram to use for finding optimal split points
*/
@SerializedName("histogram_type")
public TreeSharedTreeModelSharedTreeParametersHistogramType histogramType;
/**
* Use Platt Scaling (default) or Isotonic Regression to calculate calibrated class probabilities. Calibration can
* provide more accurate estimates of class probabilities.
*/
@SerializedName("calibrate_model")
public boolean calibrateModel;
/**
* Data for model calibration
*/
@SerializedName("calibration_frame")
public FrameKeyV3 calibrationFrame;
/**
* Calibration method to use
*/
@SerializedName("calibration_method")
public TreeCalibrationHelperCalibrationMethod calibrationMethod;
/**
* Check if response column is constant. If enabled, then an exception is thrown if the response column is a
* constant value.If disabled, then model will train regardless of the response column being a constant value or
* not.
*/
@SerializedName("check_constant_response")
public boolean checkConstantResponse;
/**
* Create checkpoints into defined directory while training process is still running. In case of cluster shutdown,
* this checkpoint can be used to restart training.
*/
@SerializedName("in_training_checkpoints_dir")
public String inTrainingCheckpointsDir;
/**
* Checkpoint the model after every so many trees. Parameter is used only when in_training_checkpoints_dir is
* defined
*/
@SerializedName("in_training_checkpoints_tree_interval")
public int inTrainingCheckpointsTreeInterval;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Destination id for this model; auto-generated if not specified.
public ModelKeyV3 modelId;
// Id of the training data frame.
public FrameKeyV3 trainingFrame;
// Id of the validation data frame.
public FrameKeyV3 validationFrame;
// Number of folds for K-fold cross-validation (0 to disable or >= 2).
public int nfolds;
// Whether to keep the cross-validation models.
public boolean keepCrossValidationModels;
// Whether to keep the predictions of the cross-validation models.
public boolean keepCrossValidationPredictions;
// Whether to keep the cross-validation fold assignment.
public boolean keepCrossValidationFoldAssignment;
// Allow parallel training of cross-validation models
public boolean parallelizeCrossValidation;
// Distribution function
public GenmodelutilsDistributionFamily distribution;
// Tweedie power for Tweedie regression, must be between 1 and 2.
public double tweediePower;
// Desired quantile for Quantile regression, must be between 0 and 1.
public double quantileAlpha;
// Desired quantile for Huber/M-regression (threshold between quadratic and linear loss, must be between 0 and 1).
public double huberAlpha;
// Response variable column.
public ColSpecifierV3 responseColumn;
// Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
// dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights
// are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data frame.
// This is typically the number of times a row is repeated, but non-integer values are supported as well. During
// training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set weight = 0
// for a row, the returned prediction frame at that row is zero and this is incorrect. To get an accurate
// prediction, remove all rows with weight == 0.
public ColSpecifierV3 weightsColumn;
// Offset column. This will be added to the combination of columns before applying the link function.
public ColSpecifierV3 offsetColumn;
// Column with cross-validation fold index assignment per observation.
public ColSpecifierV3 foldColumn;
// Cross-validation fold assignment scheme, if fold_column is not specified. The 'Stratified' option will stratify
// the folds based on the response variable, for classification problems.
public ModelParametersFoldAssignmentScheme foldAssignment;
// Encoding scheme for categorical features
public ModelParametersCategoricalEncodingScheme categoricalEncoding;
// For every categorical feature, only use this many most frequent categorical levels for model training. Only used
// for categorical_encoding == EnumLimited.
public int maxCategoricalLevels;
// Names of columns to ignore for training.
public String[] ignoredColumns;
// Ignore constant columns.
public boolean ignoreConstCols;
// Whether to score during each iteration of model training.
public boolean scoreEachIteration;
// Model checkpoint to resume training with.
public ModelKeyV3 checkpoint;
// Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
// stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
public int stoppingRounds;
// Maximum allowed runtime in seconds for model training. Use 0 to disable.
public double maxRuntimeSecs;
// Metric to use for early stopping (AUTO: logloss for classification, deviance for regression and anomaly_score for
// Isolation Forest). Note that custom and custom_increasing can only be used in GBM and DRF with the Python client.
public ScoreKeeperStoppingMetric stoppingMetric;
// Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
public double stoppingTolerance;
// Gains/Lift table number of bins. 0 means disabled.. Default value -1 means automatic binning.
public int gainsliftBins;
// Reference to custom evaluation function, format: `language:keyName=funcName`
public String customMetricFunc;
// Reference to custom distribution, format: `language:keyName=funcName`
public String customDistributionFunc;
// Automatically export generated models to this directory.
public String exportCheckpointsDir;
// Set default multinomial AUC type.
public MultinomialAucType aucType;
*/
/**
* Public constructor
*/
public SharedTreeParametersV3() {
balanceClasses = false;
maxAfterBalanceSize = 0.0f;
maxConfusionMatrixSize = 0;
ntrees = 0;
maxDepth = 0;
minRows = 0.0;
nbins = 0;
nbinsTopLevel = 0;
nbinsCats = 0;
r2Stopping = 0.0;
seed = 0L;
buildTreeOneNode = false;
colSampleRatePerTree = 0.0;
colSampleRateChangePerLevel = 0.0;
scoreTreeInterval = 0;
minSplitImprovement = 0.0;
calibrateModel = false;
checkConstantResponse = false;
inTrainingCheckpointsDir = "";
inTrainingCheckpointsTreeInterval = 0;
nfolds = 0;
keepCrossValidationModels = false;
keepCrossValidationPredictions = false;
keepCrossValidationFoldAssignment = false;
parallelizeCrossValidation = false;
tweediePower = 0.0;
quantileAlpha = 0.0;
huberAlpha = 0.0;
maxCategoricalLevels = 0;
ignoreConstCols = false;
scoreEachIteration = false;
stoppingRounds = 0;
maxRuntimeSecs = 0.0;
stoppingTolerance = 0.0;
gainsliftBins = 0;
customMetricFunc = "";
customDistributionFunc = "";
exportCheckpointsDir = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SharedTreeV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SharedTreeV3<P extends ModelParametersSchemaV3> extends ModelBuilderSchema<P> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Model builder parameters.
public P parameters;
// The algo name for this ModelBuilder.
public String algo;
// The pretty algo name for this ModelBuilder (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// Model categories this ModelBuilder can build.
public ModelCategory[] canBuild;
// Indicator whether the model is supervised or not.
public boolean supervised;
// Should the builder always be visible, be marked as beta, or only visible if the user starts up with the
// experimental flag?
public ModelBuilderBuilderVisibility visibility;
// Job Key
public JobV3 job;
// Parameter validation messages
public ValidationMessageV3[] messages;
// Count of parameter validation errors
public int errorCount;
// HTTP status to return for this build.
public int __httpStatus;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public SharedTreeV3() {
algo = "";
algoFullName = "";
supervised = false;
errorCount = 0;
__httpStatus = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/ShutdownV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ShutdownV3 extends RequestSchemaV3 {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public ShutdownV3() {
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SignificantRulesV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SignificantRulesV3 extends RequestSchemaV3 {
/**
* Model id of interest
*/
@SerializedName("model_id")
public ModelKeyV3 modelId;
/**
* The estimated coefficients and language representations (in case it is a rule) for each of the significant
* baselearners.
*/
@SerializedName("significant_rules_table")
public TwoDimTableV3 significantRulesTable;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public SignificantRulesV3() {
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SimpleRecipeResponseType.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum SimpleRecipeResponseType {
BOOL,
ENUM,
INT,
NONE,
REAL,
TIME,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SplitFrameV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SplitFrameV3 extends SchemaV3 {
/**
* Job Key
*/
public JobKeyV3 key;
/**
* Dataset
*/
public FrameKeyV3 dataset;
/**
* Split ratios - resulting number of split is ratios.length+1
*/
public double[] ratios;
/**
* Destination keys for each output frame split.
*/
@SerializedName("destination_frames")
public FrameKeyV3[] destinationFrames;
/**
* Public constructor
*/
public SplitFrameV3() {
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/StackedEnsembleModelOutputV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class StackedEnsembleModelOutputV99 extends ModelOutputSchemaV3 {
/**
* Model which combines the base_models into a stacked ensemble.
*/
public ModelKeyV3 metalearner;
/**
* Level one frame used for metalearner training.
*/
@SerializedName("levelone_frame_id")
public FrameKeyV3 leveloneFrameId;
/**
* The stacking strategy used for training.
*/
@SerializedName("stacking_strategy")
public EnsembleStackedEnsembleModelStackingStrategy stackingStrategy;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Column names
public String[] names;
// Original column names
public String[] originalNames;
// Column types
public String[] columnTypes;
// Domains for categorical columns
public String[][] domains;
// Cross-validation models (model ids)
public ModelKeyV3[] crossValidationModels;
// Cross-validation predictions, one per cv model (deprecated, use cross_validation_holdout_predictions_frame_id
// instead)
public FrameKeyV3[] crossValidationPredictions;
// Cross-validation holdout predictions (full out-of-sample predictions on training data)
public FrameKeyV3 crossValidationHoldoutPredictionsFrameId;
// Cross-validation fold assignment (each row is assigned to one holdout fold)
public FrameKeyV3 crossValidationFoldAssignmentFrameId;
// Category of the model (e.g., Binomial)
public ModelCategory modelCategory;
// Model summary
public TwoDimTableV3 modelSummary;
// Scoring history
public TwoDimTableV3 scoringHistory;
// Cross-Validation scoring history
public TwoDimTableV3[] cvScoringHistory;
// Model reproducibility information
public TwoDimTableV3[] reproducibilityInformationTable;
// Training data model metrics
public ModelMetricsBaseV3 trainingMetrics;
// Validation data model metrics
public ModelMetricsBaseV3 validationMetrics;
// Cross-validation model metrics
public ModelMetricsBaseV3 crossValidationMetrics;
// Cross-validation model metrics summary
public TwoDimTableV3 crossValidationMetricsSummary;
// Job status
public String status;
// Start time in milliseconds
public long startTime;
// End time in milliseconds
public long endTime;
// Runtime in milliseconds
public long runTime;
// Default threshold used for predictions
public double defaultThreshold;
// Help information for output fields
public Map<String,String> help;
*/
/**
* Public constructor
*/
public StackedEnsembleModelOutputV99() {
modelCategory = ModelCategory.Unknown;
status = "";
startTime = 0L;
endTime = 0L;
runTime = 0L;
defaultThreshold = 0.5;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/StackedEnsembleModelV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class StackedEnsembleModelV99 extends ModelSchemaV3<StackedEnsembleParametersV99, StackedEnsembleModelOutputV99> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// The build parameters for the model (e.g. K for KMeans).
public StackedEnsembleParametersV99 parameters;
// The build output for the model (e.g. the cluster centers for KMeans).
public StackedEnsembleModelOutputV99 output;
// Compatible frames, if requested
public String[] compatibleFrames;
// Checksum for all the things that go into building the Model.
public long checksum;
// Model key
public ModelKeyV3 modelId;
// The algo name for this Model.
public String algo;
// The pretty algo name for this Model (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// The response column name for this Model (if applicable). Is null otherwise.
public String responseColumnName;
// The treatment column name for this Model (if applicable). Is null otherwise.
public String treatmentColumnName;
// The Model's training frame key
public FrameKeyV3 dataFrame;
// Timestamp for when this model was completed
public long timestamp;
// Indicator, whether export to POJO is available
public boolean havePojo;
// Indicator, whether export to MOJO is available
public boolean haveMojo;
*/
/**
* Public constructor
*/
public StackedEnsembleModelV99() {
checksum = 0L;
algo = "";
algoFullName = "";
responseColumnName = "";
treatmentColumnName = "";
timestamp = 0L;
havePojo = false;
haveMojo = false;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/StackedEnsembleParametersV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class StackedEnsembleParametersV99 extends ModelParametersSchemaV3 {
/**
* List of models or grids (or their ids) to ensemble/stack together. Grids are expanded to individual models. If
* not using blending frame, then models must have been cross-validated using nfolds > 1, and folds must be
* identical across models.
*/
@SerializedName("base_models")
public KeyV3[] baseModels;
/**
* Type of algorithm to use as the metalearner. Options include 'AUTO' (GLM with non negative weights; if
* validation_frame is present, a lambda search is performed), 'deeplearning' (Deep Learning with default
* parameters), 'drf' (Random Forest with default parameters), 'gbm' (GBM with default parameters), 'glm' (GLM with
* default parameters), 'naivebayes' (NaiveBayes with default parameters), or 'xgboost' (if available, XGBoost with
* default parameters).
*/
@SerializedName("metalearner_algorithm")
public EnsembleMetalearnerAlgorithm metalearnerAlgorithm;
/**
* Number of folds for K-fold cross-validation of the metalearner algorithm (0 to disable or >= 2).
*/
@SerializedName("metalearner_nfolds")
public int metalearnerNfolds;
/**
* Cross-validation fold assignment scheme for metalearner cross-validation. Defaults to AUTO (which is currently
* set to Random). The 'Stratified' option will stratify the folds based on the response variable, for
* classification problems.
*/
@SerializedName("metalearner_fold_assignment")
public ModelParametersFoldAssignmentScheme metalearnerFoldAssignment;
/**
* Column with cross-validation fold index assignment per observation for cross-validation of the metalearner.
*/
@SerializedName("metalearner_fold_column")
public ColSpecifierV3 metalearnerFoldColumn;
/**
* Transformation used for the level one frame.
*/
@SerializedName("metalearner_transform")
public EnsembleStackedEnsembleModelStackedEnsembleParametersMetalearnerTransform metalearnerTransform;
/**
* Keep level one frame used for metalearner training.
*/
@SerializedName("keep_levelone_frame")
public boolean keepLeveloneFrame;
/**
* Parameters for metalearner algorithm
*/
@SerializedName("metalearner_params")
public String metalearnerParams;
/**
* Frame used to compute the predictions that serve as the training frame for the metalearner (triggers blending
* mode if provided)
*/
@SerializedName("blending_frame")
public FrameKeyV3 blendingFrame;
/**
* Seed for random numbers; passed through to the metalearner algorithm. Defaults to -1 (time-based random number)
*/
public long seed;
/**
* Specify the number of training set samples for scoring. The value must be >= 0. To use all training samples,
* enter 0.
*/
@SerializedName("score_training_samples")
public long scoreTrainingSamples;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Destination id for this model; auto-generated if not specified.
public ModelKeyV3 modelId;
// Id of the training data frame.
public FrameKeyV3 trainingFrame;
// Id of the validation data frame.
public FrameKeyV3 validationFrame;
// Number of folds for K-fold cross-validation (0 to disable or >= 2).
public int nfolds;
// Whether to keep the cross-validation models.
public boolean keepCrossValidationModels;
// Whether to keep the predictions of the cross-validation models.
public boolean keepCrossValidationPredictions;
// Whether to keep the cross-validation fold assignment.
public boolean keepCrossValidationFoldAssignment;
// Allow parallel training of cross-validation models
public boolean parallelizeCrossValidation;
// Distribution function
public GenmodelutilsDistributionFamily distribution;
// Tweedie power for Tweedie regression, must be between 1 and 2.
public double tweediePower;
// Desired quantile for Quantile regression, must be between 0 and 1.
public double quantileAlpha;
// Desired quantile for Huber/M-regression (threshold between quadratic and linear loss, must be between 0 and 1).
public double huberAlpha;
// Response variable column.
public ColSpecifierV3 responseColumn;
// Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
// dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights
// are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data frame.
// This is typically the number of times a row is repeated, but non-integer values are supported as well. During
// training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set weight = 0
// for a row, the returned prediction frame at that row is zero and this is incorrect. To get an accurate
// prediction, remove all rows with weight == 0.
public ColSpecifierV3 weightsColumn;
// Offset column. This will be added to the combination of columns before applying the link function.
public ColSpecifierV3 offsetColumn;
// Column with cross-validation fold index assignment per observation.
public ColSpecifierV3 foldColumn;
// Cross-validation fold assignment scheme, if fold_column is not specified. The 'Stratified' option will stratify
// the folds based on the response variable, for classification problems.
public ModelParametersFoldAssignmentScheme foldAssignment;
// Encoding scheme for categorical features
public ModelParametersCategoricalEncodingScheme categoricalEncoding;
// For every categorical feature, only use this many most frequent categorical levels for model training. Only used
// for categorical_encoding == EnumLimited.
public int maxCategoricalLevels;
// Names of columns to ignore for training.
public String[] ignoredColumns;
// Ignore constant columns.
public boolean ignoreConstCols;
// Whether to score during each iteration of model training.
public boolean scoreEachIteration;
// Model checkpoint to resume training with.
public ModelKeyV3 checkpoint;
// Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
// stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
public int stoppingRounds;
// Maximum allowed runtime in seconds for model training. Use 0 to disable.
public double maxRuntimeSecs;
// Metric to use for early stopping (AUTO: logloss for classification, deviance for regression and anomaly_score for
// Isolation Forest). Note that custom and custom_increasing can only be used in GBM and DRF with the Python client.
public ScoreKeeperStoppingMetric stoppingMetric;
// Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
public double stoppingTolerance;
// Gains/Lift table number of bins. 0 means disabled.. Default value -1 means automatic binning.
public int gainsliftBins;
// Reference to custom evaluation function, format: `language:keyName=funcName`
public String customMetricFunc;
// Reference to custom distribution, format: `language:keyName=funcName`
public String customDistributionFunc;
// Automatically export generated models to this directory.
public String exportCheckpointsDir;
// Set default multinomial AUC type.
public MultinomialAucType aucType;
*/
/**
* Public constructor
*/
public StackedEnsembleParametersV99() {
baseModels = new KeyV3[]{};
metalearnerAlgorithm = EnsembleMetalearnerAlgorithm.AUTO;
metalearnerNfolds = 0;
metalearnerTransform = EnsembleStackedEnsembleModelStackedEnsembleParametersMetalearnerTransform.NONE;
keepLeveloneFrame = false;
metalearnerParams = "";
seed = -1L;
scoreTrainingSamples = 10000L;
nfolds = 0;
keepCrossValidationModels = true;
keepCrossValidationPredictions = false;
keepCrossValidationFoldAssignment = false;
parallelizeCrossValidation = true;
distribution = GenmodelutilsDistributionFamily.AUTO;
tweediePower = 1.5;
quantileAlpha = 0.5;
huberAlpha = 0.9;
foldAssignment = ModelParametersFoldAssignmentScheme.AUTO;
categoricalEncoding = ModelParametersCategoricalEncodingScheme.AUTO;
maxCategoricalLevels = 10;
ignoreConstCols = true;
scoreEachIteration = false;
stoppingRounds = 0;
maxRuntimeSecs = 0.0;
stoppingMetric = ScoreKeeperStoppingMetric.AUTO;
stoppingTolerance = 0.001;
gainsliftBins = -1;
customMetricFunc = "";
customDistributionFunc = "";
exportCheckpointsDir = "";
aucType = MultinomialAucType.AUTO;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/StackedEnsembleV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class StackedEnsembleV99 extends ModelBuilderSchema<StackedEnsembleParametersV99> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Model builder parameters.
public StackedEnsembleParametersV99 parameters;
// The algo name for this ModelBuilder.
public String algo;
// The pretty algo name for this ModelBuilder (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// Model categories this ModelBuilder can build.
public ModelCategory[] canBuild;
// Indicator whether the model is supervised or not.
public boolean supervised;
// Should the builder always be visible, be marked as beta, or only visible if the user starts up with the
// experimental flag?
public ModelBuilderBuilderVisibility visibility;
// Job Key
public JobV3 job;
// Parameter validation messages
public ValidationMessageV3[] messages;
// Count of parameter validation errors
public int errorCount;
// HTTP status to return for this build.
public int __httpStatus;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public StackedEnsembleV99() {
algo = "";
algoFullName = "";
supervised = false;
errorCount = 0;
__httpStatus = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/SteamMetricsV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class SteamMetricsV3 extends RequestSchemaV3 {
/**
* Steam metrics API version
*/
public long version;
/**
* Number of milliseconds that the cluster has been idle
*/
@SerializedName("idle_millis")
public long idleMillis;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public SteamMetricsV3() {
version = 0L;
idleMillis = 0L;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/StepDefinitionV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class StepDefinitionV99 {
/**
* Name of the step provider (usually, this is also the name of an algorithm).
*/
public String name;
/**
* An alias representing a predefined list of steps to be executed.
*/
public H2oautomlStepDefinitionAlias alias;
/**
* The list of steps to be executed (Mutually exclusive with alias).
*/
public StepV99[] steps;
/**
* Public constructor
*/
public StepDefinitionV99() {
name = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/StepV99.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class StepV99 {
/**
* The id of the step (must be unique per step provider).
*/
public String id;
/**
* The group of execution of the given step (groups are executed in ascending order of priority).Steps with group=0
* are skipped. Defaults to -1 to use the default group assigned to the step id.
*/
public int group;
/**
* The relative weight for the given step (can impact time and/or number of models allocated for this step). Steps
* with weight=0 are skipped. Defaults to -1 to use the default weight assigned to the step id.
*/
public int weight;
/**
* Public constructor
*/
public StepV99() {
id = "";
group = -1;
weight = -1;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/StreamingSchema.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class StreamingSchema extends SchemaV3 {
/**
* Public constructor
*/
public StreamingSchema() {
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/StringPairV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class StringPairV3 extends SchemaV3 {
/**
* Value A
*/
public String a;
/**
* Value B
*/
public String b;
/**
* Public constructor
*/
public StringPairV3() {
a = "";
b = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TabulateV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TabulateV3 extends SchemaV3 {
/**
* Dataset
*/
public FrameKeyV3 dataset;
/**
* Predictor
*/
public ColSpecifierV3 predictor;
/**
* Response
*/
public ColSpecifierV3 response;
/**
* Observation weights (optional)
*/
public ColSpecifierV3 weight;
/**
* Number of bins for predictor column
*/
@SerializedName("nbins_predictor")
public int nbinsPredictor;
/**
* Number of bins for response column
*/
@SerializedName("nbins_response")
public int nbinsResponse;
/**
* Counts table
*/
@SerializedName("count_table")
public TwoDimTableV3 countTable;
/**
* Response table
*/
@SerializedName("response_table")
public TwoDimTableV3 responseTable;
/**
* Public constructor
*/
public TabulateV3() {
nbinsPredictor = 20;
nbinsResponse = 10;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TargetEncoderModelOutputV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TargetEncoderModelOutputV3 extends ModelOutputSchemaV3 {
/**
* Mapping between input column(s) and their corresponding target encoded output column(s). Please note that there
* can be multiple columns on the input/from side if columns grouping was used, and there can also be multiple
* columns on the output/to side if the target was multiclass.
*/
@SerializedName("input_to_output_columns")
public ColumnsMappingV3[] inputToOutputColumns;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Column names
public String[] names;
// Original column names
public String[] originalNames;
// Column types
public String[] columnTypes;
// Domains for categorical columns
public String[][] domains;
// Cross-validation models (model ids)
public ModelKeyV3[] crossValidationModels;
// Cross-validation predictions, one per cv model (deprecated, use cross_validation_holdout_predictions_frame_id
// instead)
public FrameKeyV3[] crossValidationPredictions;
// Cross-validation holdout predictions (full out-of-sample predictions on training data)
public FrameKeyV3 crossValidationHoldoutPredictionsFrameId;
// Cross-validation fold assignment (each row is assigned to one holdout fold)
public FrameKeyV3 crossValidationFoldAssignmentFrameId;
// Category of the model (e.g., Binomial)
public ModelCategory modelCategory;
// Model summary
public TwoDimTableV3 modelSummary;
// Scoring history
public TwoDimTableV3 scoringHistory;
// Cross-Validation scoring history
public TwoDimTableV3[] cvScoringHistory;
// Model reproducibility information
public TwoDimTableV3[] reproducibilityInformationTable;
// Training data model metrics
public ModelMetricsBaseV3 trainingMetrics;
// Validation data model metrics
public ModelMetricsBaseV3 validationMetrics;
// Cross-validation model metrics
public ModelMetricsBaseV3 crossValidationMetrics;
// Cross-validation model metrics summary
public TwoDimTableV3 crossValidationMetricsSummary;
// Job status
public String status;
// Start time in milliseconds
public long startTime;
// End time in milliseconds
public long endTime;
// Runtime in milliseconds
public long runTime;
// Default threshold used for predictions
public double defaultThreshold;
// Help information for output fields
public Map<String,String> help;
*/
/**
* Public constructor
*/
public TargetEncoderModelOutputV3() {
status = "";
startTime = 0L;
endTime = 0L;
runTime = 0L;
defaultThreshold = 0.0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TargetEncoderModelV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TargetEncoderModelV3 extends ModelSchemaV3<TargetEncoderParametersV3, TargetEncoderModelOutputV3> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// The build parameters for the model (e.g. K for KMeans).
public TargetEncoderParametersV3 parameters;
// The build output for the model (e.g. the cluster centers for KMeans).
public TargetEncoderModelOutputV3 output;
// Compatible frames, if requested
public String[] compatibleFrames;
// Checksum for all the things that go into building the Model.
public long checksum;
// Model key
public ModelKeyV3 modelId;
// The algo name for this Model.
public String algo;
// The pretty algo name for this Model (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// The response column name for this Model (if applicable). Is null otherwise.
public String responseColumnName;
// The treatment column name for this Model (if applicable). Is null otherwise.
public String treatmentColumnName;
// The Model's training frame key
public FrameKeyV3 dataFrame;
// Timestamp for when this model was completed
public long timestamp;
// Indicator, whether export to POJO is available
public boolean havePojo;
// Indicator, whether export to MOJO is available
public boolean haveMojo;
*/
/**
* Public constructor
*/
public TargetEncoderModelV3() {
checksum = 0L;
algo = "";
algoFullName = "";
responseColumnName = "";
treatmentColumnName = "";
timestamp = 0L;
havePojo = false;
haveMojo = false;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TargetEncoderParametersV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TargetEncoderParametersV3 extends ModelParametersSchemaV3 {
/**
* List of categorical columns or groups of categorical columns to encode. When groups of columns are specified,
* each group is encoded as a single column (interactions are created internally).
*/
@SerializedName("columns_to_encode")
public String[][] columnsToEncode;
/**
* If true, the original non-encoded categorical features will remain in the result frame.
*/
@SerializedName("keep_original_categorical_columns")
public boolean keepOriginalCategoricalColumns;
/**
* If true, enables blending of posterior probabilities (computed for a given categorical value) with prior
* probabilities (computed on the entire set). This allows to mitigate the effect of categorical values with small
* cardinality. The blending effect can be tuned using the `inflection_point` and `smoothing` parameters.
*/
public boolean blending;
/**
* Inflection point of the sigmoid used to blend probabilities (see `blending` parameter). For a given categorical
* value, if it appears less that `inflection_point` in a data sample, then the influence of the posterior
* probability will be smaller than the prior.
*/
@SerializedName("inflection_point")
public double inflectionPoint;
/**
* Smoothing factor corresponds to the inverse of the slope at the inflection point on the sigmoid used to blend
* probabilities (see `blending` parameter). If smoothing tends towards 0, then the sigmoid used for blending turns
* into a Heaviside step function.
*/
public double smoothing;
/**
* Data leakage handling strategy used to generate the encoding. Supported options are:
* 1) "none" (default) - no holdout, using the entire training frame.
* 2) "leave_one_out" - current row's response value is subtracted from the per-level frequencies pre-calculated on
* the entire training frame.
* 3) "k_fold" - encodings for a fold are generated based on out-of-fold data.
*/
@SerializedName("data_leakage_handling")
public H2otargetencodingTargetEncoderModelDataLeakageHandlingStrategy dataLeakageHandling;
/**
* The amount of noise to add to the encoded column. Use 0 to disable noise, and -1 (=AUTO) to let the algorithm
* determine a reasonable amount of noise.
*/
public double noise;
/**
* Seed used to generate the noise. By default, the seed is chosen randomly.
*/
public long seed;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Destination id for this model; auto-generated if not specified.
public ModelKeyV3 modelId;
// Id of the training data frame.
public FrameKeyV3 trainingFrame;
// Id of the validation data frame.
public FrameKeyV3 validationFrame;
// Number of folds for K-fold cross-validation (0 to disable or >= 2).
public int nfolds;
// Whether to keep the cross-validation models.
public boolean keepCrossValidationModels;
// Whether to keep the predictions of the cross-validation models.
public boolean keepCrossValidationPredictions;
// Whether to keep the cross-validation fold assignment.
public boolean keepCrossValidationFoldAssignment;
// Allow parallel training of cross-validation models
public boolean parallelizeCrossValidation;
// Distribution function
public GenmodelutilsDistributionFamily distribution;
// Tweedie power for Tweedie regression, must be between 1 and 2.
public double tweediePower;
// Desired quantile for Quantile regression, must be between 0 and 1.
public double quantileAlpha;
// Desired quantile for Huber/M-regression (threshold between quadratic and linear loss, must be between 0 and 1).
public double huberAlpha;
// Response variable column.
public ColSpecifierV3 responseColumn;
// Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
// dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights
// are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data frame.
// This is typically the number of times a row is repeated, but non-integer values are supported as well. During
// training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set weight = 0
// for a row, the returned prediction frame at that row is zero and this is incorrect. To get an accurate
// prediction, remove all rows with weight == 0.
public ColSpecifierV3 weightsColumn;
// Offset column. This will be added to the combination of columns before applying the link function.
public ColSpecifierV3 offsetColumn;
// Column with cross-validation fold index assignment per observation.
public ColSpecifierV3 foldColumn;
// Cross-validation fold assignment scheme, if fold_column is not specified. The 'Stratified' option will stratify
// the folds based on the response variable, for classification problems.
public ModelParametersFoldAssignmentScheme foldAssignment;
// Encoding scheme for categorical features
public ModelParametersCategoricalEncodingScheme categoricalEncoding;
// For every categorical feature, only use this many most frequent categorical levels for model training. Only used
// for categorical_encoding == EnumLimited.
public int maxCategoricalLevels;
// Names of columns to ignore for training.
public String[] ignoredColumns;
// Ignore constant columns.
public boolean ignoreConstCols;
// Whether to score during each iteration of model training.
public boolean scoreEachIteration;
// Model checkpoint to resume training with.
public ModelKeyV3 checkpoint;
// Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
// stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
public int stoppingRounds;
// Maximum allowed runtime in seconds for model training. Use 0 to disable.
public double maxRuntimeSecs;
// Metric to use for early stopping (AUTO: logloss for classification, deviance for regression and anomaly_score for
// Isolation Forest). Note that custom and custom_increasing can only be used in GBM and DRF with the Python client.
public ScoreKeeperStoppingMetric stoppingMetric;
// Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
public double stoppingTolerance;
// Gains/Lift table number of bins. 0 means disabled.. Default value -1 means automatic binning.
public int gainsliftBins;
// Reference to custom evaluation function, format: `language:keyName=funcName`
public String customMetricFunc;
// Reference to custom distribution, format: `language:keyName=funcName`
public String customDistributionFunc;
// Automatically export generated models to this directory.
public String exportCheckpointsDir;
// Set default multinomial AUC type.
public MultinomialAucType aucType;
*/
/**
* Public constructor
*/
public TargetEncoderParametersV3() {
keepOriginalCategoricalColumns = true;
blending = false;
inflectionPoint = 10.0;
smoothing = 20.0;
dataLeakageHandling = H2otargetencodingTargetEncoderModelDataLeakageHandlingStrategy.None;
noise = 0.01;
seed = -1L;
nfolds = 0;
keepCrossValidationModels = true;
keepCrossValidationPredictions = false;
keepCrossValidationFoldAssignment = false;
parallelizeCrossValidation = true;
distribution = GenmodelutilsDistributionFamily.AUTO;
tweediePower = 1.5;
quantileAlpha = 0.5;
huberAlpha = 0.9;
foldAssignment = ModelParametersFoldAssignmentScheme.AUTO;
categoricalEncoding = ModelParametersCategoricalEncodingScheme.AUTO;
maxCategoricalLevels = 10;
ignoreConstCols = false;
scoreEachIteration = false;
stoppingRounds = 0;
maxRuntimeSecs = 0.0;
stoppingMetric = ScoreKeeperStoppingMetric.AUTO;
stoppingTolerance = 0.001;
gainsliftBins = -1;
customMetricFunc = "";
customDistributionFunc = "";
exportCheckpointsDir = "";
aucType = MultinomialAucType.AUTO;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TargetEncoderTransformParametersV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TargetEncoderTransformParametersV3 extends SchemaV3 {
/**
* Target Encoder model to use.
*/
public ModelKeyV3 model;
/**
* Frame to transform.
*/
public FrameKeyV3 frame;
/**
* Force encoding mode for training data: when using a leakage handling strategy different from None, training data
* should be transformed with this flag set to true (Defaults to false).
*/
@SerializedName("as_training")
public boolean asTraining;
/**
* Enables or disables blending. Defaults to the value assigned at model creation.
*/
public boolean blending;
/**
* Inflection point. Defaults to the value assigned at model creation.
*/
@SerializedName("inflection_point")
public double inflectionPoint;
/**
* Smoothing. Defaults to the value assigned at model creation.
*/
public double smoothing;
/**
* Noise. Defaults to the value assigned at model creation.
*/
public double noise;
/**
* Public constructor
*/
public TargetEncoderTransformParametersV3() {
asTraining = false;
blending = false;
inflectionPoint = -1.0;
smoothing = -1.0;
noise = -2.0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TargetEncoderV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TargetEncoderV3 extends ModelBuilderSchema<TargetEncoderParametersV3> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Model builder parameters.
public TargetEncoderParametersV3 parameters;
// The algo name for this ModelBuilder.
public String algo;
// The pretty algo name for this ModelBuilder (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// Model categories this ModelBuilder can build.
public ModelCategory[] canBuild;
// Indicator whether the model is supervised or not.
public boolean supervised;
// Should the builder always be visible, be marked as beta, or only visible if the user starts up with the
// experimental flag?
public ModelBuilderBuilderVisibility visibility;
// Job Key
public JobV3 job;
// Parameter validation messages
public ValidationMessageV3[] messages;
// Count of parameter validation errors
public int errorCount;
// HTTP status to return for this build.
public int __httpStatus;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public TargetEncoderV3() {
algo = "";
algoFullName = "";
supervised = false;
errorCount = 0;
__httpStatus = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TimelineEventEventType.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TimelineEventEventType {
heartbeat,
io,
network_msg,
unknown,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TimelineV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TimelineV3 extends RequestSchemaV3 {
/**
* Current time in millis.
*/
public long now;
/**
* This node
*/
public String self;
/**
* recorded timeline events
*/
public EventV3[] events;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public TimelineV3() {
now = 0L;
self = "";
events = new EventV3[]{};
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreeCalibrationHelperCalibrationMethod.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreeCalibrationHelperCalibrationMethod {
AUTO,
IsotonicRegression,
PlattScaling,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreeHandlerPlainLanguageRules.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreeHandlerPlainLanguageRules {
AUTO,
FALSE,
TRUE,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreeSharedTreeModelSharedTreeParametersHistogramType.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreeSharedTreeModelSharedTreeParametersHistogramType {
AUTO,
QuantilesGlobal,
Random,
RoundRobin,
UniformAdaptive,
UniformRobust,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreeStatsV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TreeStatsV3 extends SchemaV3 {
/**
* minDepth
*/
@SerializedName("min_depth")
public int minDepth;
/**
* maxDepth
*/
@SerializedName("max_depth")
public int maxDepth;
/**
* meanDepth
*/
@SerializedName("mean_depth")
public float meanDepth;
/**
* minLeaves
*/
@SerializedName("min_leaves")
public int minLeaves;
/**
* maxLeaves
*/
@SerializedName("max_leaves")
public int maxLeaves;
/**
* meanLeaves
*/
@SerializedName("mean_leaves")
public float meanLeaves;
/**
* Public constructor
*/
public TreeStatsV3() {
minDepth = 0;
maxDepth = 0;
meanDepth = 0.0f;
minLeaves = 0;
maxLeaves = 0;
meanLeaves = 0.0f;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreeV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TreeV3 extends SchemaV3 {
/**
* Key of the model the desired tree belongs to
*/
public ModelKeyV3 model;
/**
* Index of the tree in the model.
*/
@SerializedName("tree_number")
public int treeNumber;
/**
* Name of the class of the tree. Ignored for regression and binomial.
*/
@SerializedName("tree_class")
public String treeClass;
/**
* Whether to generate plain language rules.
*/
@SerializedName("plain_language_rules")
public TreeHandlerPlainLanguageRules plainLanguageRules;
/**
* Left child nodes in the tree
*/
@SerializedName("left_children")
public int[] leftChildren;
/**
* Right child nodes in the tree
*/
@SerializedName("right_children")
public int[] rightChildren;
/**
* Number of the root node
*/
@SerializedName("root_node_id")
public int rootNodeId;
/**
* Split thresholds (numeric and possibly categorical columns)
*/
public float[] thresholds;
/**
* Names of the column of the split
*/
public String[] features;
/**
* Which way NA Splits (LEFT, RIGHT, NA)
*/
public String[] nas;
/**
* Description of the tree's nodes
*/
public String[] descriptions;
/**
* Categorical levels on the edge from the parent node
*/
public int[][] levels;
/**
* Prediction values on terminal nodes
*/
public float[] predictions;
/**
* Plain language rules representation of a trained decision tree
*/
@SerializedName("tree_decision_path")
public String treeDecisionPath;
/**
* Plain language rules that were used in a particular prediction
*/
@SerializedName("decision_paths")
public String[] decisionPaths;
/**
* Public constructor
*/
public TreeV3() {
treeNumber = 0;
treeClass = "";
rootNodeId = 0;
treeDecisionPath = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreeupliftUpliftDRFModelUpliftDRFParametersUpliftMetricType.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreeupliftUpliftDRFModelUpliftDRFParametersUpliftMetricType {
AUTO,
ChiSquared,
Euclidean,
KL,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreexgboostXGBoostModelXGBoostParametersBackend.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreexgboostXGBoostModelXGBoostParametersBackend {
auto,
cpu,
gpu,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreexgboostXGBoostModelXGBoostParametersBooster.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreexgboostXGBoostModelXGBoostParametersBooster {
dart,
gblinear,
gbtree,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreexgboostXGBoostModelXGBoostParametersDMatrixType.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreexgboostXGBoostModelXGBoostParametersDMatrixType {
auto,
dense,
sparse,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreexgboostXGBoostModelXGBoostParametersDartNormalizeType.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreexgboostXGBoostModelXGBoostParametersDartNormalizeType {
forest,
tree,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreexgboostXGBoostModelXGBoostParametersDartSampleType.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreexgboostXGBoostModelXGBoostParametersDartSampleType {
uniform,
weighted,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreexgboostXGBoostModelXGBoostParametersGrowPolicy.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreexgboostXGBoostModelXGBoostParametersGrowPolicy {
depthwise,
lossguide,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TreexgboostXGBoostModelXGBoostParametersTreeMethod.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum TreexgboostXGBoostModelXGBoostParametersTreeMethod {
approx,
auto,
exact,
hist,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TwoDimTableV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TwoDimTableV3 extends SchemaV3 {
/**
* Table Name
*/
public String name;
/**
* Table Description
*/
public String description;
/**
* Column Specification
*/
public ColumnSpecsBase[] columns;
/**
* Number of Rows
*/
public int rowcount;
/**
* Table Data (col-major)
*/
public Object[][] data;
/**
* Public constructor
*/
public TwoDimTableV3() {
name = "";
description = "";
rowcount = 0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/TypeaheadV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class TypeaheadV3 extends RequestSchemaV3 {
/**
* training_frame
*/
public String src;
/**
* limit
*/
public int limit;
/**
* matches
*/
public String[] matches;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public TypeaheadV3() {
src = "";
limit = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/UnlockKeysV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class UnlockKeysV3 extends RequestSchemaV3 {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public UnlockKeysV3() {
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/UpliftDRFModelOutputV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class UpliftDRFModelOutputV3 extends SharedTreeModelOutputV3 {
/**
* Default thresholds to calculate AUUC metric. If validation is enabled, thresholds from validation metrics is
* saved here. Otherwise thresholds are from training metrics.
*/
@SerializedName("default_auuc_thresholds")
public double[] defaultAuucThresholds;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Variable Importances
public TwoDimTableV3 variableImportances;
// The Intercept term, the initial model function value to which trees make adjustments
public double initF;
// Column names
public String[] names;
// Original column names
public String[] originalNames;
// Column types
public String[] columnTypes;
// Domains for categorical columns
public String[][] domains;
// Cross-validation models (model ids)
public ModelKeyV3[] crossValidationModels;
// Cross-validation predictions, one per cv model (deprecated, use cross_validation_holdout_predictions_frame_id
// instead)
public FrameKeyV3[] crossValidationPredictions;
// Cross-validation holdout predictions (full out-of-sample predictions on training data)
public FrameKeyV3 crossValidationHoldoutPredictionsFrameId;
// Cross-validation fold assignment (each row is assigned to one holdout fold)
public FrameKeyV3 crossValidationFoldAssignmentFrameId;
// Category of the model (e.g., Binomial)
public ModelCategory modelCategory;
// Model summary
public TwoDimTableV3 modelSummary;
// Scoring history
public TwoDimTableV3 scoringHistory;
// Cross-Validation scoring history
public TwoDimTableV3[] cvScoringHistory;
// Model reproducibility information
public TwoDimTableV3[] reproducibilityInformationTable;
// Training data model metrics
public ModelMetricsBaseV3 trainingMetrics;
// Validation data model metrics
public ModelMetricsBaseV3 validationMetrics;
// Cross-validation model metrics
public ModelMetricsBaseV3 crossValidationMetrics;
// Cross-validation model metrics summary
public TwoDimTableV3 crossValidationMetricsSummary;
// Job status
public String status;
// Start time in milliseconds
public long startTime;
// End time in milliseconds
public long endTime;
// Runtime in milliseconds
public long runTime;
// Default threshold used for predictions
public double defaultThreshold;
// Help information for output fields
public Map<String,String> help;
*/
/**
* Public constructor
*/
public UpliftDRFModelOutputV3() {
initF = 0.0;
status = "";
startTime = 0L;
endTime = 0L;
runTime = 0L;
defaultThreshold = 0.0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/UpliftDRFModelV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class UpliftDRFModelV3 extends SharedTreeModelV3<UpliftDRFParametersV3, UpliftDRFModelOutputV3> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// The build parameters for the model (e.g. K for KMeans).
public UpliftDRFParametersV3 parameters;
// The build output for the model (e.g. the cluster centers for KMeans).
public UpliftDRFModelOutputV3 output;
// Compatible frames, if requested
public String[] compatibleFrames;
// Checksum for all the things that go into building the Model.
public long checksum;
// Model key
public ModelKeyV3 modelId;
// The algo name for this Model.
public String algo;
// The pretty algo name for this Model (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// The response column name for this Model (if applicable). Is null otherwise.
public String responseColumnName;
// The treatment column name for this Model (if applicable). Is null otherwise.
public String treatmentColumnName;
// The Model's training frame key
public FrameKeyV3 dataFrame;
// Timestamp for when this model was completed
public long timestamp;
// Indicator, whether export to POJO is available
public boolean havePojo;
// Indicator, whether export to MOJO is available
public boolean haveMojo;
*/
/**
* Public constructor
*/
public UpliftDRFModelV3() {
checksum = 0L;
algo = "";
algoFullName = "";
responseColumnName = "";
treatmentColumnName = "";
timestamp = 0L;
havePojo = false;
haveMojo = false;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/UpliftDRFParametersV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class UpliftDRFParametersV3 extends SharedTreeParametersV3 {
/**
* Number of variables randomly sampled as candidates at each split. If set to -1, defaults to sqrt{p} for
* classification and p/3 for regression (where p is the # of predictors
*/
public int mtries;
/**
* Row sample rate per tree (from 0.0 to 1.0)
*/
@SerializedName("sample_rate")
public double sampleRate;
/**
* Define the column which will be used for computing uplift gain to select best split for a tree. The column has to
* divide the dataset into treatment (value 1) and control (value 0) groups.
*/
@SerializedName("treatment_column")
public String treatmentColumn;
/**
* Divergence metric used to find best split when building an uplift tree.
*/
@SerializedName("uplift_metric")
public TreeupliftUpliftDRFModelUpliftDRFParametersUpliftMetricType upliftMetric;
/**
* Metric used to calculate Area Under Uplift Curve.
*/
@SerializedName("auuc_type")
public AUUCType auucType;
/**
* Number of bins to calculate Area Under Uplift Curve.
*/
@SerializedName("auuc_nbins")
public int auucNbins;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Balance training data class counts via over/under-sampling (for imbalanced data).
public boolean balanceClasses;
// Desired over/under-sampling ratios per class (in lexicographic order). If not specified, sampling factors will be
// automatically computed to obtain class balance during training. Requires balance_classes.
public float[] classSamplingFactors;
// Maximum relative size of the training data after balancing class counts (can be less than 1.0). Requires
// balance_classes.
public float maxAfterBalanceSize;
// [Deprecated] Maximum size (# classes) for confusion matrices to be printed in the Logs
public int maxConfusionMatrixSize;
// Number of trees.
public int ntrees;
// Maximum tree depth (0 for unlimited).
public int maxDepth;
// Fewest allowed (weighted) observations in a leaf.
public double minRows;
// For numerical columns (real/int), build a histogram of (at least) this many bins, then split at the best point
public int nbins;
// For numerical columns (real/int), build a histogram of (at most) this many bins at the root level, then decrease
// by factor of two per level
public int nbinsTopLevel;
// For categorical columns (factors), build a histogram of this many bins, then split at the best point. Higher
// values can lead to more overfitting.
public int nbinsCats;
// r2_stopping is no longer supported and will be ignored if set - please use stopping_rounds, stopping_metric and
// stopping_tolerance instead. Previous version of H2O would stop making trees when the R^2 metric equals or exceeds
// this
public double r2Stopping;
// Seed for pseudo random number generator (if applicable)
public long seed;
// Run on one node only; no network overhead but fewer cpus used. Suitable for small datasets.
public boolean buildTreeOneNode;
// A list of row sample rates per class (relative fraction for each class, from 0.0 to 1.0), for each tree
public double[] sampleRatePerClass;
// Column sample rate per tree (from 0.0 to 1.0)
public double colSampleRatePerTree;
// Relative change of the column sampling rate for every level (must be > 0.0 and <= 2.0)
public double colSampleRateChangePerLevel;
// Score the model after every so many trees. Disabled if set to 0.
public int scoreTreeInterval;
// Minimum relative improvement in squared error reduction for a split to happen
public double minSplitImprovement;
// What type of histogram to use for finding optimal split points
public TreeSharedTreeModelSharedTreeParametersHistogramType histogramType;
// Use Platt Scaling (default) or Isotonic Regression to calculate calibrated class probabilities. Calibration can
// provide more accurate estimates of class probabilities.
public boolean calibrateModel;
// Data for model calibration
public FrameKeyV3 calibrationFrame;
// Calibration method to use
public TreeCalibrationHelperCalibrationMethod calibrationMethod;
// Check if response column is constant. If enabled, then an exception is thrown if the response column is a
// constant value.If disabled, then model will train regardless of the response column being a constant value or
// not.
public boolean checkConstantResponse;
// Create checkpoints into defined directory while training process is still running. In case of cluster shutdown,
// this checkpoint can be used to restart training.
public String inTrainingCheckpointsDir;
// Checkpoint the model after every so many trees. Parameter is used only when in_training_checkpoints_dir is
// defined
public int inTrainingCheckpointsTreeInterval;
// Destination id for this model; auto-generated if not specified.
public ModelKeyV3 modelId;
// Id of the training data frame.
public FrameKeyV3 trainingFrame;
// Id of the validation data frame.
public FrameKeyV3 validationFrame;
// Number of folds for K-fold cross-validation (0 to disable or >= 2).
public int nfolds;
// Whether to keep the cross-validation models.
public boolean keepCrossValidationModels;
// Whether to keep the predictions of the cross-validation models.
public boolean keepCrossValidationPredictions;
// Whether to keep the cross-validation fold assignment.
public boolean keepCrossValidationFoldAssignment;
// Allow parallel training of cross-validation models
public boolean parallelizeCrossValidation;
// Distribution function
public GenmodelutilsDistributionFamily distribution;
// Tweedie power for Tweedie regression, must be between 1 and 2.
public double tweediePower;
// Desired quantile for Quantile regression, must be between 0 and 1.
public double quantileAlpha;
// Desired quantile for Huber/M-regression (threshold between quadratic and linear loss, must be between 0 and 1).
public double huberAlpha;
// Response variable column.
public ColSpecifierV3 responseColumn;
// Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
// dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights
// are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data frame.
// This is typically the number of times a row is repeated, but non-integer values are supported as well. During
// training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set weight = 0
// for a row, the returned prediction frame at that row is zero and this is incorrect. To get an accurate
// prediction, remove all rows with weight == 0.
public ColSpecifierV3 weightsColumn;
// Offset column. This will be added to the combination of columns before applying the link function.
public ColSpecifierV3 offsetColumn;
// Column with cross-validation fold index assignment per observation.
public ColSpecifierV3 foldColumn;
// Cross-validation fold assignment scheme, if fold_column is not specified. The 'Stratified' option will stratify
// the folds based on the response variable, for classification problems.
public ModelParametersFoldAssignmentScheme foldAssignment;
// Encoding scheme for categorical features
public ModelParametersCategoricalEncodingScheme categoricalEncoding;
// For every categorical feature, only use this many most frequent categorical levels for model training. Only used
// for categorical_encoding == EnumLimited.
public int maxCategoricalLevels;
// Names of columns to ignore for training.
public String[] ignoredColumns;
// Ignore constant columns.
public boolean ignoreConstCols;
// Whether to score during each iteration of model training.
public boolean scoreEachIteration;
// Model checkpoint to resume training with.
public ModelKeyV3 checkpoint;
// Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the
// stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
public int stoppingRounds;
// Maximum allowed runtime in seconds for model training. Use 0 to disable.
public double maxRuntimeSecs;
// Metric to use for early stopping (AUTO: logloss for classification, deviance for regression and anomaly_score for
// Isolation Forest). Note that custom and custom_increasing can only be used in GBM and DRF with the Python client.
public ScoreKeeperStoppingMetric stoppingMetric;
// Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
public double stoppingTolerance;
// Gains/Lift table number of bins. 0 means disabled.. Default value -1 means automatic binning.
public int gainsliftBins;
// Reference to custom evaluation function, format: `language:keyName=funcName`
public String customMetricFunc;
// Reference to custom distribution, format: `language:keyName=funcName`
public String customDistributionFunc;
// Automatically export generated models to this directory.
public String exportCheckpointsDir;
// Set default multinomial AUC type.
public MultinomialAucType aucType;
*/
/**
* Public constructor
*/
public UpliftDRFParametersV3() {
mtries = -2;
sampleRate = 0.632;
treatmentColumn = "treatment";
upliftMetric = TreeupliftUpliftDRFModelUpliftDRFParametersUpliftMetricType.AUTO;
auucType = AUUCType.AUTO;
auucNbins = -1;
balanceClasses = false;
maxAfterBalanceSize = 5.0f;
maxConfusionMatrixSize = 20;
ntrees = 50;
maxDepth = 20;
minRows = 1.0;
nbins = 20;
nbinsTopLevel = 1024;
nbinsCats = 1024;
r2Stopping = 1.7976931348623157e+308;
seed = -1L;
buildTreeOneNode = false;
colSampleRatePerTree = 1.0;
colSampleRateChangePerLevel = 1.0;
scoreTreeInterval = 0;
minSplitImprovement = 1e-05;
histogramType = TreeSharedTreeModelSharedTreeParametersHistogramType.AUTO;
calibrateModel = false;
calibrationMethod = TreeCalibrationHelperCalibrationMethod.AUTO;
checkConstantResponse = true;
inTrainingCheckpointsDir = "";
inTrainingCheckpointsTreeInterval = 1;
nfolds = 0;
keepCrossValidationModels = true;
keepCrossValidationPredictions = false;
keepCrossValidationFoldAssignment = false;
parallelizeCrossValidation = true;
distribution = GenmodelutilsDistributionFamily.AUTO;
tweediePower = 1.5;
quantileAlpha = 0.5;
huberAlpha = 0.9;
foldAssignment = ModelParametersFoldAssignmentScheme.AUTO;
categoricalEncoding = ModelParametersCategoricalEncodingScheme.AUTO;
maxCategoricalLevels = 10;
ignoreConstCols = true;
scoreEachIteration = false;
stoppingRounds = 0;
maxRuntimeSecs = 0.0;
stoppingMetric = ScoreKeeperStoppingMetric.AUTO;
stoppingTolerance = 0.001;
gainsliftBins = -1;
customMetricFunc = "";
customDistributionFunc = "";
exportCheckpointsDir = "";
aucType = MultinomialAucType.AUTO;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/UpliftDRFV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class UpliftDRFV3 extends SharedTreeV3<UpliftDRFParametersV3> {
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Model builder parameters.
public UpliftDRFParametersV3 parameters;
// The algo name for this ModelBuilder.
public String algo;
// The pretty algo name for this ModelBuilder (e.g., Generalized Linear Model, rather than GLM).
public String algoFullName;
// Model categories this ModelBuilder can build.
public ModelCategory[] canBuild;
// Indicator whether the model is supervised or not.
public boolean supervised;
// Should the builder always be visible, be marked as beta, or only visible if the user starts up with the
// experimental flag?
public ModelBuilderBuilderVisibility visibility;
// Job Key
public JobV3 job;
// Parameter validation messages
public ValidationMessageV3[] messages;
// Count of parameter validation errors
public int errorCount;
// HTTP status to return for this build.
public int __httpStatus;
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public UpliftDRFV3() {
algo = "";
algoFullName = "";
supervised = false;
errorCount = 0;
__httpStatus = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/UtilExportFileFormat.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
public enum UtilExportFileFormat {
csv,
parquet,
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/ValidationMessageV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ValidationMessageV3 extends SchemaV3 {
/**
* Type of validation message (ERROR, WARN, INFO, HIDE)
*/
@SerializedName("message_type")
public String messageType;
/**
* Field to which the message applies
*/
@SerializedName("field_name")
public String fieldName;
/**
* Message text
*/
public String message;
/**
* Public constructor
*/
public ValidationMessageV3() {
messageType = "";
fieldName = "";
message = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/VarImpV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class VarImpV3 extends SchemaV3 {
/**
* Variable importance of individual variables
*/
public float[] varimp;
/**
* Names of variables
*/
public String[] names;
/**
* Public constructor
*/
public VarImpV3() {
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/WaterMeterCpuTicksV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class WaterMeterCpuTicksV3 extends RequestSchemaV3 {
/**
* Index of node to query ticks for (0-based)
*/
public int nodeidx;
/**
* array of tick counts per core
*/
@SerializedName("cpu_ticks")
public long[][] cpuTicks;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public WaterMeterCpuTicksV3() {
nodeidx = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
0
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings
|
java-sources/ai/h2o/h2o-bindings/3.46.0.7/water/bindings/pojos/WaterMeterIoV3.java
|
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class WaterMeterIoV3 extends RequestSchemaV3 {
/**
* Index of node to query ticks for (0-based)
*/
public int nodeidx;
/**
* array of IO info
*/
@SerializedName("persist_stats")
public IoStatsEntry[] persistStats;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public WaterMeterIoV3() {
nodeidx = 0;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}
|
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