A SURVEY ON CLASSIFICATION TECHNIQUES FOR TEXT MINING

The development of the World Wide Web it is no longer feasible for a user can understand all the data coming from classify into categories. The expansion of information and power automatic classification of data and textual data gains increasingly and give high performance. In this paper five important text classifications are described Naive Bayesian, K-Nearest Neighbour, Support Vector Machine, Decision Tree and Regression. Which are categorized the text data into pre define class. The target of the paper is to study different classification techniques and finding the classification accuracy for different datasets. An efficient and effective text documents into mutually exclusive categories.