First spam detector exercise

naive_bayes.py

+from sklearn.naive_bayes import MultinomialNB
+from sklearn.ensemble import AdaBoostClassifier
+import pandas as pd
+import numpy as np
+
+data = pd.read_csv('./spambase/spambase.data').values
+np.random.shuffle(data)
+X = data[:, :48]
+Y = data[:, -1]
+
+X_train = X[:-100,]
+X_test = X[-100:,]
+Y_train = Y[:-100,]
+Y_test = Y[-100:,]
+
+model = MultinomialNB()
+model.fit(X_train, Y_train)
+print("Classification rate:", model.score(X_test, Y_test))
+
+ada_model = AdaBoostClassifier()
+ada_model.fit(X_train, Y_train)
+print("Classification rate with Ada", ada_model.score(X_test, Y_test))
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