SURVEY ON CLASSIFIER MODELS FOR TEXT CLASSSFICATION

Abstract

This paper gives a comparison of frequently used classifier models for text classification in the recent years. Text classification is the task of assigning pre-defined categories to free text documents. With the advent of technology we come across a large scale and high dimensional text corpus. It is a challenge to perform text classification on such corpus, in presence of imbalanced class distribution and noisy term features. There are a number of models for performing text classification with various degrees of success. We can simplify the task of text classification by using the following models: Support Vector Machine (SVM), k-nearest neighbor (KNN), Centroid (Rocchio), Naïve Bayes classifiers.