Performance Comparison of Different Classifier Models In Sentiment Analysis

Abstract

The goal of this paper is to analyse the performance of the different machine learning algorithms for data mining . In this study, 20 Machine Learning models were benchmarked for their accuracy and speed performance on different hardware architectures. These are applied when applied to 2 multinomial datasets differing broadly in size and complexity. Therefore, our study performs a benchmarking of different classification algorithms highlighting the adequacy and efficiency of different classifiers