Training results - 20251208_152749
Browse files- .gitattributes +3 -0
- training_results/confusion_matrices_20251208_143505.png +0 -0
- training_results/evaluation_metrics_20251208_143505.csv +6 -0
- training_results/metrics_summary_20251208_143505.png +0 -0
- training_results/model_20251208_143505.keras +3 -0
- training_results/predictions_20251208_143505.npz +3 -0
- training_results/results_20251208_143505.json +57 -0
- training_results/roc_curves_20251208_143505.png +3 -0
- training_results/threshold_comparison_20251208_143505.csv +21 -0
- training_results/threshold_optimization_20251208_143505.json +199 -0
- training_results/threshold_optimization_20251208_143505.png +3 -0
.gitattributes
CHANGED
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@@ -74,3 +74,6 @@ training_results/model_20251127_080822.keras filter=lfs diff=lfs merge=lfs -text
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training_results/model_20251127_081239.keras filter=lfs diff=lfs merge=lfs -text
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training_results/roc_curves_20251127_081239.png filter=lfs diff=lfs merge=lfs -text
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training_results/threshold_optimization_20251127_081239.png filter=lfs diff=lfs merge=lfs -text
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training_results/model_20251127_081239.keras filter=lfs diff=lfs merge=lfs -text
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training_results/roc_curves_20251127_081239.png filter=lfs diff=lfs merge=lfs -text
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training_results/threshold_optimization_20251127_081239.png filter=lfs diff=lfs merge=lfs -text
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training_results/model_20251208_143505.keras filter=lfs diff=lfs merge=lfs -text
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| 78 |
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training_results/roc_curves_20251208_143505.png filter=lfs diff=lfs merge=lfs -text
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| 79 |
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training_results/threshold_optimization_20251208_143505.png filter=lfs diff=lfs merge=lfs -text
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training_results/confusion_matrices_20251208_143505.png
ADDED
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training_results/evaluation_metrics_20251208_143505.csv
ADDED
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@@ -0,0 +1,6 @@
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| 1 |
+
Class,Precision,Recall,F1-Score,ROC-AUC,Support
|
| 2 |
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Myocarditis,0.5989847715736041,0.325068870523416,0.42142857142857143,0.8440567087695262,363
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| 3 |
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Cardiomyopathy,0.75,0.5783132530120482,0.6530612244897959,0.9473786112717755,83
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Kawasaki,0.75,0.05454545454545454,0.1016949152542373,0.8188957768786269,110
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CHD,0.7495854063018242,0.5873944119558154,0.6586520947176685,0.8660338136468052,1539
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Healthy,0.8631950573698146,0.9119731443491235,0.8869139385145551,0.8588173294081306,5362
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training_results/metrics_summary_20251208_143505.png
ADDED
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training_results/model_20251208_143505.keras
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:917ba68730a05907bdd268bbad4ec239a872ede5d5808fe93df6cbff2467ff49
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size 5990753
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training_results/predictions_20251208_143505.npz
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 597316
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training_results/results_20251208_143505.json
ADDED
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@@ -0,0 +1,57 @@
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{
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"timestamp": "20251208_143505",
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| 3 |
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"disease_classes": [
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| 4 |
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"Myocarditis",
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| 5 |
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"Cardiomyopathy",
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| 6 |
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"Kawasaki",
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| 7 |
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"CHD",
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"Healthy"
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],
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"micro_f1": 0.8174282386791807,
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"macro_f1": 0.4869882509249547,
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"mean_roc_auc": 0.8670364479949729
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},
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"per_class_metrics": {
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"Myocarditis": {
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"precision": 0.5989847715736041,
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"recall": 0.325068870523416,
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"f1_score": 0.42142857142857143,
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"roc_auc": 0.8440567087695262,
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"support": 363
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"Cardiomyopathy": {
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"precision": 0.75,
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"recall": 0.5783132530120482,
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"f1_score": 0.6530612244897959,
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"roc_auc": 0.9473786112717755,
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"support": 83
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| 34 |
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},
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"Kawasaki": {
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| 36 |
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"precision": 0.75,
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"recall": 0.05454545454545454,
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"f1_score": 0.1016949152542373,
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"roc_auc": 0.8188957768786269,
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| 40 |
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"support": 110
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| 41 |
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},
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| 42 |
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"CHD": {
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| 43 |
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"precision": 0.7495854063018242,
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"recall": 0.5873944119558154,
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"f1_score": 0.6586520947176685,
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"roc_auc": 0.8660338136468052,
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"support": 1539
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| 48 |
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},
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| 49 |
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"Healthy": {
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| 50 |
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"precision": 0.8631950573698146,
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"recall": 0.9119731443491235,
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"f1_score": 0.8869139385145551,
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"roc_auc": 0.8588173294081306,
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"support": 5362
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}
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training_results/roc_curves_20251208_143505.png
ADDED
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Git LFS Details
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training_results/threshold_comparison_20251208_143505.csv
ADDED
|
@@ -0,0 +1,21 @@
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| 1 |
+
Strategy,Class,Threshold,Precision,Recall,F1-Score
|
| 2 |
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Baseline (0.5),Myocarditis,0.5,0.5989847715736041,0.325068870523416,0.42142857142857143
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Baseline (0.5),Cardiomyopathy,0.5,0.75,0.5783132530120482,0.6530612244897959
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Baseline (0.5),Kawasaki,0.5,0.75,0.05454545454545454,0.1016949152542373
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Baseline (0.5),CHD,0.5,0.7495854063018242,0.5873944119558154,0.6586520947176685
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Baseline (0.5),Healthy,0.5,0.8631950573698146,0.9119731443491235,0.8869139385145551
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F1-Maximization,Myocarditis,0.4099999999999998,0.5614754098360656,0.3774104683195592,0.4514003294892916
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F1-Maximization,Cardiomyopathy,0.2799999999999999,0.684931506849315,0.6024096385542169,0.6410256410256411
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| 9 |
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F1-Maximization,Kawasaki,0.1,0.1261682242990654,0.24545454545454545,0.16666666666666666
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| 10 |
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F1-Maximization,CHD,0.44999999999999984,0.7134052388289677,0.6016894087069525,0.6528022559041241
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| 11 |
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F1-Maximization,Healthy,0.20999999999999996,0.8238358326756117,0.973330846698993,0.8923655638197828
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| 12 |
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Youden's J,Myocarditis,0.11,0.26632522407170295,0.5730027548209367,0.36363636363636365
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| 13 |
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Youden's J,Cardiomyopathy,0.1,0.5656565656565656,0.6746987951807228,0.6153846153846154
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| 14 |
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Youden's J,Kawasaki,0.1,0.1261682242990654,0.24545454545454545,0.16666666666666666
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Youden's J,CHD,0.2799999999999999,0.6084959816303099,0.6887589343729694,0.6461444681499543
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| 16 |
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Youden's J,Healthy,0.6599999999999997,0.8865206236431814,0.8377471092875792,0.8614440502445105
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| 17 |
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Recall-Prioritized,Myocarditis,0.05,0.13735691987513007,0.7272727272727273,0.23107221006564552
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Recall-Prioritized,Cardiomyopathy,0.05,0.45185185185185184,0.7349397590361446,0.5596330275229358
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Recall-Prioritized,Kawasaki,0.05,0.08966861598440545,0.41818181818181815,0.1476725521669342
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Recall-Prioritized,CHD,0.17000000000000004,0.49086479902557856,0.7855750487329435,0.6041979010494752
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Recall-Prioritized,Healthy,0.21000000000000002,0.8238358326756117,0.973330846698993,0.8923655638197828
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training_results/threshold_optimization_20251208_143505.json
ADDED
|
@@ -0,0 +1,199 @@
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| 1 |
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{
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| 2 |
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"timestamp": "20251208_143505",
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"Myocarditis",
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"Cardiomyopathy",
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"Kawasaki",
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"CHD",
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"Healthy"
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],
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"optimized_thresholds": {
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"f1_max": {
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"recall_priority": {
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"CHD": 0.17000000000000004,
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}
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},
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"comparison": {
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"Baseline (0.5)": {
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"f1": 0.42142857142857143,
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"threshold": 0.5
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"Cardiomyopathy": {
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"threshold": 0.5
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},
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"Kawasaki": {
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"recall": 0.05454545454545454,
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"f1": 0.1016949152542373,
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"threshold": 0.5
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"CHD": {
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"recall": 0.5873944119558154,
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"f1": 0.6586520947176685,
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"threshold": 0.5
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"Healthy": {
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"recall": 0.9119731443491235,
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"f1": 0.8869139385145551,
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"threshold": 0.5
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}
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|
| 198 |
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|
| 199 |
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training_results/threshold_optimization_20251208_143505.png
ADDED
|
Git LFS Details
|