Question: 5.0.5 2e) Prediction Predict the labels for both the training and test samples (the 'X' data). You will need to use MR_tfidf_clf . predict (...)

5.0.5 2e) Prediction Predict the labels for both the training and test samples (the 'X' data). You will need to use MR_tfidf_clf . predict (...) Name the predicted labels on training samples as MR_pred_train_tfidf_Y. Name the predicted labels on testing samples as MR_pred_test_tfidf_Y Note: this may take a few seconds to run. # your code here raise NotImplementedError Again, we use classification_report to check the performance on the training set. : # Your classifier should be able to reach above 86% accuracy. print (classification_report (MR_train_tfidf_Y, MR_pred_train_tfidf_Y)) Again, check performance on the test set: : # Your classifier should be able to reach around 71% accuracy. print (classification_report (MR_test_tfidf_Y, MR_pred_test_tfidf_Y) ) precision, recall, _, _ = precision_recall_fscore_support (MR_train_tfidf_Y, MR_pred_train_tfidf_Y) assert np . isclose (precision [0] , 0. 85, 0.02) assert np . isclose (precision [1] , 0. 89, 0.02)

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