Techniques for Improving the Performance of Naive Bayes for Text Classification

摘要

Naive Bayes is often used in text classification applications and experiments because of its simplicity and effectiveness. However, its performance is often degraded because it does not model text well, and by inappropriate feature selection and the lack of reliable confidence scores. We address these problems and show that they can be solved by some simple corrections. We demonstrate that our simple modifications are able to improve the performance of Naive Bayes for text classification significantly.