Data clustering algorithm based on feature weighting theory
FEI Xian-ju
LI Hong
TIAN Guo-zhong
Abstract：Aiming at the problem that the initial clustering number and center are difficult to be determined in the data clustering opertion of data mining process, a fuzzy weighting clustering algorithm based on the soft subspace as well as the competition and combination mechanism was proposed. Through rewriting the objective function of soft subspace clustering algorithm and combining the size of data clusters, the competition and combination operation was carried out for the data clusters, and the clustering treatment of data was achieved. The results show that the proposed algorithm can accurately perform the clustering of data samples, and the clustering results are independent on the initial clustering number and center. The algorithm can meet the need in high dimensional data clustering processing and has the great practical value.
Keywords：data miningdata clusteringfeature weightingsoft subspace clusteringcombination and competition mechanismfuzzy clustering algorithmclustering centerclustering number
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 77-81 )