Feature Selection Techniques for Text Classification

Abstract

Text classification of documents refers to classifying documents to one or more predefined classes. One of the most important steps in text classification is feature selection. In text classification, feature selection is a strategy that can be used to increase the efficiency and accuracy of classification. Feature selection techniques can be classified into two basic categories: filtering techniques and wrapper techniques. Filtering techniques are independent of the learning algorithm. But wrapper methods uses from learning algorithm as the evaluation function. In this paper we review some effectiveness feature selection researches and show review results of these in a table form