Sentiment Analyis of Indian Movie Review with Various Feature Selection Techniques
Abstract-In the first place, Sentiment analysis and opinion mining is an emerging area of research for analysing web data and capturing the sentiment of the users.In addition,research presents sentiments analysis on Indian movie review corpus using machine learning classifier. In contrast, Bayesian Classifier has been used in this study for testing feature selection mechanics. This classifier is trained on the words/features for the purpose of, the corpus extracted using five feature selection algorithms (Chi-square, Info-gain, Gain-Ratio, One-R and relief attribute) important to realize, and a comparative study have been performed amongst them. The classifier and feature selection approaches were evaluated by two different metrics (F-Value, and False Positive). Results of this study show that: for maximum number of features, Relief -F feature selection approach is found to be goodwith better F-value, Low FP Rate. In addition for the less number of features, One-R was better than Relief-F. In the final analysis, electronic document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet.
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