Empirical Study of Online News Classification Using Machine Learning Approaches








Abstract

The developed text classification system is designed to automate news classification process. Text corpus for training and testing the system is formed from Azerbaijani news articles. The system will be useful for online news categorization and automatic news labeling for news agencies. Naive Bayes, Support Vector Machines, and Artificial Neural Networks have been implemented to solve the news classification problem. Moreover, a number of approaches such as stemming, stop word removal, feature reduction have been implemented for both performance and accuracy improvements.


Modules


Algorithms

Machine learning algorithms


Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL