After comparing attributes reduction of rough sets and parameters reduction of soft sets,this paper presents a method of parameters reduction in soft set based on invariability of optimal choice objects.

Study on data reduction and rules discovery based on convex Rough set;

Study on the Building Checks Price Based on Data Reduction;

Data Reduction and the Application in Auditing of the Social Security Network;

Collaborative filtering recommendation model based on effective dimension reduction and K-means clustering

Most machine learning tasks confront the problem of dimensionality reduction for extracting meaningful features and processing convenience.

This survey introduces general solutions to every step of the categorization process including document modeling,feature selection,dimensionality reduction,classification scheme selection.

In this dissertation, some key issues on manifold learning have been studied, the main contributions are summarized as follows:Baed on the analysis of PCA and MVU, we propose a new nonlinear dimensionality reduction method called distinguishing variance embedding (DVE).