A Method of Reducing Features Based on Orthogonal Transforming in Text Classification
文本分类中一种基于正交变换的特征降维方法

Discuss a method of reducing the text features based on orthogonal transforming.Then,we analyze the characteristic about feature selection and feature extraction.In virtue of decomposing the matrix,we demonstrate the principle and the theory foundation about the reduce of dimensions based on Fisher.We discuss the relation of PCA and SVD.The test shows that this method has a better precision in the text categorization.