One of the most important tools nowadays for spreading information is news. That is considering as elementary need along with the revolution of technology. The classification of different news content has a great effect on different groups of human in society. Text classification is an important technique for data mining. Text classification classifies text into predefined classes. In this paper, BBC news, which consists of total 2225-distribution news, has been classified into five categories, which are business, entertainment, politics, sport, and technology. Three classification algorithms were applied to the BBC news dataset; which is Multinomial Naive Bayes (MNB), K Nearest Neighbor's (KNN), and Stochastic Gradient Descent learning (SGD). SGD was found the best with precision equal to 98%.
Volume 12 | Issue 1
Pages: 148-152
DOI: 10.5373/JARDCS/V12I1/20201023