Research Article Open Access

A Comparative study of Classifiers’ Performance for Gender Classification

Abstract

-Reviewer gender classification is an important function of Sentiment Analysis system. Both supervised and unsupervised approach may be applied for gender classification. In this paper we used supervised machine learning approach. We use three different classifiers, namely Naïve Bayes Classifier, Maximum Entropy Classifier and Decision Tree Classifier respectively. We trained all classifiers using same training set and same feature function. Then we test the Accuracy, Precision, Recall, F1-measure of all test cases using same test set. Finally, we make an comparative study about performance of this classifiers. KEYWORDS: naïve bayes classifier; maxent classifier; decision tree classifier; text classification; gender classification; classifier

Santanu Modak , Abhoy Chand Mondal

To read the full article Download Full Article | Visit Full Article