Naive Bayes classifiers are a remarkably successful ML algorithmfor learning to classify text documents.
The objective of your multinomial Naïve Bayes algorithm is to: (i)Build a model by using the negativeand positive moviereviews contained in the trainfolder. (ii)It should then takein the movie reviews in the folder testand classify them. (iii)You should compare the predictions of your model with the true class label and calculatethe accuracy of the model for positive and negative movie reviews.. The dataset contains 25,000 movie reviewsin the trainfolder, split evenly between positive and negative.
Model is created using “bag of words” method. Data from the dataset is fetched, cleaned and stored in a table with the conditional probabilities. Test is carried out using the data from test dataset.