NAIVE BAYES BINARY CLASSIFICATION FOR FILM REVIEW
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Date
2023-01
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Abstract
Online streaming services provide thousands of movie collections that can be
watched by customers, viewers usually choose films based on reviews and ratings.
To save time in the selection of good programs, there needs to be a tool to classify
the various reviews available to choose which films are worth watching.
Classification is an important topic in machine learning and data mining. In this
study we use the naïve bayes algorithm which is one of the most efficient and
effective algorithms for classification. The data set used in this study is the IMDB
film review data taken from [4], as many as 50000 data that has been given 2 types
of classification labels, namely "negative" and "positive".It can be concluded that
the accuracy of the Naïve Bayes algorithm by applying the Multinomial and
Beroulli methods is able to classify film reviews well in all test scenarios with the
best accuracy achieved is 84%.