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IMDB movie review polarity using Naive Bayes Classifier
Develop a naive Bayes algorithm-based machine learning model that predicts sentiment or polarity of an IMDB movie review.
Introduction:
Naive Bayes is an algorithm that uses Baye’s theorem. Baye’s theorem is a formula that calculates a probability by counting the frequency of given values or combinations of values in a data set [6]. If A represents the prior events, and B represents the dependent event then Bayes’ Theorem can be stated as in equation
Bayes Theorem:
here x if for different words in the review text, Ck is for the class label
p(Ck|x): the probability of class label given text review words x
review text(x) can be represented as {x1,x2,x3, …….. ,xn}
p(Ck|x) ∝ p(Ck|x1,x2,x3, …….. ,xn}
About IMDB movie review dataset:
Data source: https://www.kaggle.com/utathya/imdb-review-dataset
The IMDB Movie Review Dataset consists of text reviews with data frame named as ‘data’
