the results depicted in figure - show the top features responsible for the model making decision of predicting this review as positive based on the contentthe reviewer really liked this model and also it was real cult classic among certain age groups in our final analysiswe will look at the model interpretation of an example where the model makes wrong prediction in [ ]doc_index interpret_classification_model_prediction(doc_index=doc_indexcorpus=norm_test_ reviewscorpus=test_reviewsprediction_labels=test_ sentimentsexplainer_obj=explainertest document index actual sentimentnegative predicted sentiment['positive'reviewwhen first saw this film in cinema years agoi loved it still think the directing and cinematography are excellentas is the music but it' really the script that has over the time started to bother me more and more find emma thompson' writing selfabsorbed and unfaithful to the original bookshe has reduced marianne to side-charactera second fiddle to her much too oldmuch too severe elinor she in the movie is given many sort of 'focus moments'and often they appear to be there just to show off thompson herself do understand her cutting off several characters from the bookbut leaving out the one scene where willoughby in the book is redeemedfor someone who red and cherished the book long before the moviethose are the things always difficult to digest as for the actorsi love kate winslet as marianne she is not given the best script in the world to work with but she still pulls it up gracefullywithout too much sentimentality alan rickman is greata bit old perhapsbut he plays the role beautifully and elizabeth spriggsshe is absolutely fantastic as always model prediction probabilities('negative' ('positive' figure - model interpretation for our classification model' incorrect prediction