BCC NEWS Classification Comparison between Naïve Bayes, Support Vector Machine, Recurrent Neural Network

摘要

Data Classification is used to determine the category to which data belongs. In the present era, due to technology and information, NEWS is easily accessible through online sources. In Day to day life Data is accessed by users through many sources like information media, computer media and many more. Usually data will also be available in unorganized form and can be converted to a structure form. In order to convert the data into structured form Data Pre-Processing techniques like punctuation removal, stop word removal, stemming, lemmatizing the words, removing special characters are used and further it is classified. In this research work various data classification models like Naïve Bayes, Support Vector Machine, and Logistic regression are compared to identify best module which gives accurate results in NEWS classification.