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Published in:
2011 | OriginalPaper | Chapter
A Technique for Improving the Performance of Naive Bayes Text Classification
Authors : Yuqian Jiang, Huaizhong Lin, Xuesong Wang, Dongming Lu
Published in: Web Information Systems and Mining
Publisher: Springer Berlin Heidelberg
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Naive Bayes classifier is widely used in text classification tasks, and it can perform surprisingly well, it is often regarded as a baseline. But previous researches show that the skewed distribution of training collection may cause poor results in text classification. This paper presents a new method to deal with this situation. We introduce a conditional probability which takes into account both the information of the whole corpus and each category. Our proposed method performs well in the standard benchmark collections, competing with the state-of-the-art text classifiers especially for the skewed data.