text mining and text analytics accuracy of %and our model seems to perform better than that let' look at what it uses to determine the categories by digging into the most informative model features print(classifier show_most_informative_features( )figure shows the top terms capable of distinguishing between the two categories figure the most important terms in the naive bayes classification model the term "datais given heavy weight and seems to be the most important indicator of whether topic belongs in the data science category terms such as "scene,"season,"king,"tv,and "killare good indications the topic is game of thrones rather than data science all these things make perfect senseso the model passed both the accuracy and the sanity check the naive bayes does wellso let' have look at the decision tree in the following listing listing decision tree model training and evaluation create confusion matrix based on classification results and actual labels train decision tree classifier test classifier accuracy classifier nltk decisiontreeclassifier train(trainnltk classify accuracy(classifier testclassified_data classifier classify_many(prepared_holdout_datacm nltk confusionmatrix(holdout_data_labelsclassified_data print cm show confusion matrix attempt to classify holdout data (scoring