Text classification based on SMO and fuzzy model

In this article we propose a text classification system using chi-value as feature selection method and SMO (sequential minimal optimization) algorithm as classifier. In addition, we use fuzzy model of fuzzy concept to describe documents' classified label and entropy to calculate the uncertainty of a document's classification result. Experimental results demonstrated that the proposed method can reach 87% or higher accuracy of text classification.