Upload epurethim_159.py

epurethim_159.py

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+# -*- coding: utf-8 -*-
+"""epurethim.159
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1UmqJMfDY_e89v6dh4maq9aobuj5vz79k
+"""
+
+import pandas as pd
+from sklearn.feature_extraction.text import CountVectorizer
+from sklearn.model_selection import train_test_split
+from sklearn.naive_bayes import MultinomialNB
+from sklearn.metrics import accuracy_score
+
+dataset = pd.read_csv('/content/emails.csv')
+
+dataset.head()
+
+vectorizer = CountVectorizer()
+X = vectorizer.fit_transform(dataset['text'])
+
+X_train, X_test, y_train, y_test = train_test_split(X, dataset['spam'], test_size=0.2)
+
+model = MultinomialNB()
+model.fit(X_train, y_train)
+
+yPred = model.predict(X_test)
+
+accuracy = accuracy_score(y_test, yPred)
+print(accuracy)
+
+def predictMessage(message):
+  messageVector = vectorizer.transform([message])
+  prediction = model.predict(messageVector)
+  return 'Spam' if prediction[0] == 1 else 'Ham'
+
+userMessage = input('Enter text to predict:')
+prediction = predictMessage(userMessage)
+print(f'The message is {prediction}')