Sentiment Analysis is one of the major areas in text analytics. It primarily focuses on the recognition and categorization of opinions. Sentiment analysis is the way by which we mine the reviews given by people on different events, products, movies and many more. People rely on the reviews provided by the users of the product before shopping. Likewise people depend on the reviews of a movie before watching it. In this work, we have shown how regression algorithm work on the sentiment analysis of movie reviews and we also which regression algorithm is better for sentiment analysis. The regression algorithm which we have implemented is Random Forest, Ridge, Linear and ElasticNet. The dataset which we used for sentiment analysis is based on movie reviews also known as IMDB dataset and the parameters which we have used for analysis is mean square error and R squared error. From the result, it can be easily concluded that regression analysis with the best accuracy can be considered as a benchmark for all the other algorithms.

Sentiment Analysis, Regression, Naïve Bayes, Random forest, Features

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