SCAD Algorithm and Its Application in Analyse of Bank Loan
Feature weighting can be considered an extension of feature selection. Traditional methods of feature weighting assume that feature relevance is invariant over the tasks domain. As a result, they learn a single set of weight for the entire data set. In this paper, a proposed algorithm has been used, which is called Simultaneous Clustering and Attribute Discrimination (SCAD) and performs clustering and feature weighting simultaneously. First, the algorithm is analyzed in detail , on this basis, through a series of compare experiments, confirms this algorithm to have the high clustering precision; Finally, the algorithm is applied in the analyzing of the bank loan repaid information, that can efficiently discover the weight association of the main factors in loan information and realize potential customer.
feature weighting simultaneous clustering subspace clustering precision loan analysis
Chen Xiaojie Dong Huailin Wu Qingfeng
Software School of Xiamen University Fujian Province 361005, China
国际会议
第四届国际计算机新科技与教育学术会议(2009 4th International Conference on Computer Science & Education)
南京
英文
1934-1939
2009-07-25（万方平台首次上网日期，不代表论文的发表时间）