Bangla text document categorization using Stochastic Gradient Descent (SGD) classifier

Abstract

This paper describes the Bangla Document Categorization using Stochastic Gradient Descent (SGD) classifier. Here, document categorization is the task in which text documents are classified into one or more of predefined categories based on their contents. The proposed system can be divided into three steps: 1. feature extraction incorporating term frequency (TF) and inverse document frequency (IDF), 2. classifier design using the Stochastic Gradient Descent (SGD) algorithm by learning the distinct features, and 3. performance measure using F1-score. In the experiments on BDNews24 documents, it is observed that our proposed method provides higher accuracy in comparison with the methods based on Support Vector Machine (SVM) and Naive Bayesian (NB) classifier.