This document compares the performance of five text classification algorithms (SVM, Naive Bayes, K-Nearest Neighbors, Decision Tree, Rocchio) on news article datasets. It finds that an SVM classifier achieves the highest accuracy on the datasets tested, with accuracies of 86.7%, 75.6%, and 97.6% on the Twenty Newsgroups, Reuters, and BBC News datasets respectively. The document also evaluates and compares the training times and testing times of the classifiers on the different datasets.