期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：5
出版社：S&S Publications
摘要：Reviewer gender classification is an important function of Sentiment Analysis system. Both supervisedand unsupervised approach may be applied for gender classification. In this paper we used supervised machine learningapproach. We use three different classifiers, namely Naïve Bayes Classifier, Maximum Entropy Classifier and DecisionTree Classifier respectively. We trained all classifiers using same training set and same feature function. Then we testthe Accuracy, Precision, Recall, F1-measure of all test cases using same test set. Finally, we make an comparativestudy about performance of this classifiers.
关键词：naïve bayes classifier; maxent classifier; decision tree classifier; text classification; gender;classification; classifier
