alexa Abstract | A Comparative study of ClassifiersÂ’ Performance for Gender Classification
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

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Research Article Open Access

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

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Author(s): Santanu Modak , Abhoy Chand Mondal

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