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Performance Analysis of Machine Learning Algorithms for Movie Review
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 177 - Number 36 |
| Year of Publication: 2020 |
| Authors: Arafat Habib Quraishi |
10.5120/ijca2020919839
|
Arafat Habib Quraishi . Performance Analysis of Machine Learning Algorithms for Movie Review. International Journal of Computer Applications. 177, 36 ( Feb 2020), 7-10. DOI=10.5120/ijca2020919839
Abstract
In this paper, we have evaluated the performance of four machine learning algorithms in terms of sentiment analysis in the IMDB review dataset. Among these algorithms, two are neural network based and two are non-neural network based. We used binary classification for sentiment analysis in IMDB reviews and examined all the four algorithms to detect whether the sentiment of the text is positive or negative. Among the neural network based approaches, we applied LSTM and GRU. We found that GRU performed better than LSTM. Among the non-neural network based algorithms, we applied Multinomial Naïve Bayes and Support Vector Machine. We found that SVM outperformed Multinomial Naïve Bayes. Among these four algorithms, GRU performed the best with an accuracy of 89.0%.
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