Classification of News Articles using Gradient Boosting based Deep Learning Model

The Newspaper articles offer us insights into several news in today’s world. With the popularization of the internet, people are directly influenced by the content they surf on the internet in their daily life and online news is not among an exception. It necessitates the need to classify such news article for its readily availability. In this paper we propose a novel method named Long short-term memory-Gradient boosting (LSTM-GB) deep learning model for classification of news articles and compare the result with existing traditional classifiers. Furthermore, the proposed model attains 99.8% accuracy which outplays other classifiers.