Feature Selection in Text Classification Via SVM and LSI.

Text classification is a problem of assigning a document into one or more predefined classes. One of the most interesting issues in text categorization is feature selection. This paper proposes a novel approach in feature selection based on support vector machine(SVM) and latent semantic indexing(LSI), which can identify LSI-subspace that is suited for classification. Experimental results show that the proposed method can achieve higher classification accuracies and is of less training and prediction time. [ABSTRACT FROM AUTHOR]