期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2016
卷号：13
期号：3
出版社：IJCSI Press
摘要：Automatic management of ever increasing online digital data is a major challenge for computer science, which can be solved by using machine learning technique called automatic text classification. Automatic text classification is the process of assigning newly arrived text document to one or more predefined categories. Various feature selection and text classification techniques are available in machine learning literature. Various researchers have tried, to improve the accuracy of classification and reduce the time required, by combining different classification techniques and feature selection techniques under them. This generation of new technique by combination of existing techniques is known as Hybrid text classification. This paper aims to focus and discuss our study of the popular feature selection and text classification techniques available in machine learning literature at the same time discusses the various existing hybrid text classification techniques that are applied in the field of text document classification.
关键词：Hybrid text classification; Feature Selection; K Nearest Neighbor; Decision Tree; Naive Bayes; Support Vector Machine; Neural Network; Centroid Based Classifier; Vector Space Model.
