Study on Opinion Mining Framework Using Proposed RB-Bayes Model for Text Classification

Authors

  • Rajni Bhalla Department of Computer Application, Lovely Professional University, India.
  • Amandeep Bagga Department of Computer Application, Lovely Professional University, India.

DOI:

https://doi.org/10.9734/bpi/naer/v9/2986F

Keywords:

Confusion matrix, hotencoder, naive bayes, RB-bayes, SVM

Abstract

Everybody is active on social media and their motive is not only too active on social media but also to generate information. Before purchasing anything, we always check reviews on social media. Information mining is a capable idea with incredible potential to anticipate future patterns and conduct. It alludes to the extraction of concealed information from vast data sets by utilizing procedures like factual examination, machine learning, grouping, neural systems and genetic algorithms. In naive baye’s, there exists a problem of zero likelihood. This paper proposed RB-Bayes method based on baye’s theorem for prediction to remove problem of zero likelihood. We also compare our method with few existing methods i.e. naive baye’s and SVM. We demonstrate that this technique is better than some current techniques and specifically can analyze data sets in better way. At the point when the proposed approach is tried on genuine data-sets, the outcomes got improved accuracy in most cases. RB-Bayes calculation having precision 83,333.

Published

2021-08-03

How to Cite

Rajni Bhalla, & Amandeep Bagga. (2021). Study on Opinion Mining Framework Using Proposed RB-Bayes Model for Text Classification. New Approaches in Engineering Research Vol. 9, 99–109. https://doi.org/10.9734/bpi/naer/v9/2986F