This project pertains to the classification of news articles into their corresponding topics which have been extracted from the BBC news dataset(http://mlg.ucd.ie/datasets/bbc.html) comprised of 2225 documents from the BBC news website corresponding to stories in five topical areas from the years 2004-2005 with five class labels namely business, entertainment, politics, sport and tech. Five classifiers namely Random Forest, Multinomial Naive Bayes, Support Vector, Feed-forward and Convolutional Neural networks have been compared using cross-validation and their performance on a test data set has been compared.
