Research of Text Categorization on WEKA

摘要

The choice of algorithm is a key text categorization problem. In order to evaluation synthetically, analyzed three popular text categorization algorithm that are naive Bayes (NB), decision tree(DT) and support vector machines(SVM). Carried on simulation experiment used the open source data mining tool of Weka. Experimental results show some significant conclusions: The performance of three classification methods are better, including Support vector machine classification of the best performance, highest precision and recall, naive Bayes second, the minimum Decision tree. Also found that classification performance associated not only the choice of the classification algorithm but also the differences between corpus categories.