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In SVM you use clf_svm.fit(X_train_tfidf, training_data.flag) In MNB you use clf_mnB = MultinomialNB().fit(X_train, y_train)
clf_svm.fit(X_train_tfidf, training_data.flag)
clf_mnB = MultinomialNB().fit(X_train, y_train)
Why fitting is different?
The text was updated successfully, but these errors were encountered:
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In SVM you use
clf_svm.fit(X_train_tfidf, training_data.flag)
In MNB you use
clf_mnB = MultinomialNB().fit(X_train, y_train)
Why fitting is different?
The text was updated successfully, but these errors were encountered: