Text Classification for News Group using Machine Learning
Abstract
Text classification for news group using machine learning is useful to extract the data Robotized content arrangement has been considered as an essential technique to oversee and process an immense measure of reports in advanced structures that are broad and constantly expanding. When all is said in done, content arrangement assumes a significant job in data extraction and rundown, content recovery, and question answering. This research will outline the fundamental traits of the technology involved. In regards to the above classification strategies, Naïve Bayes is potentially good at serving as a text classification model due to its simplicity.