Comparison of auto encoder model over Naive Bayes algorithm and to improve analysis rate in opinion-rank review system

Applying Natural Language Processing techniques to the Opinion ranking dataset—a dataset concerned with the real-time classification and prediction of emotions—in order to increase the evaluation accuracy rate. The Gpower 80% approach will be used to evaluate two sets of algorithms: one set using Auto Encoder and another set using Naive Bayes. In every group, you’ll find ten examples. When compared to the Naive Bayes Algorithm, the suggested Novel Auto-Encoder method achieves a higher classification accuracy of 88.6%. The auto-encoder and Naive Bayes Algorithm do not show statistical significance with a p-value of 0.408. Novel Auto-Encoder outperformed Naive Bayes Algorithm in improving the analysis rate.