Text feature extraction and classifier optimization are two key problems for text categorization, in order to improve correct rate of text classification, this paper proposes a text classification model based on Clustering Weighted （CW） and Least Square Support Vector Machine （LSSVM） optimized by the Cuckoo Search （CS） algorithm. TF-IDF algorithm is used to calcu- late the feature weights, the feature is weighted by words position and features are clustered to reduced feature redundancy, the LSSVM is used to build text classifier which is...
