|Table of Contents|

An Improved Strategy of Active Semi-supervisionK-means Clustering Algorithm(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2018年02期
Page:
56-
Research Field:
计算机与信息工程
Publishing date:

Info

Title:
An Improved Strategy of Active Semi-supervisionK-means Clustering Algorithm
Author(s):
Lü Feng; Chai Bianfang; Li Wenbin; Wang Yao
School of Information Engineering,Hebei GEO University,Shijiazhuang 050031,China
Keywords:
active semi-supervised clustering; pairwise constrained clustering; improved algorithm
PACS:
TP181
DOI:
10.3969/j.issn.1672-1292.2018.02.008
Abstract:
The classic APCKmeans(active pairwise constrained K-means)algorithm constructs the must-link constraint set and the cannot-link constraint set as the supervised information by Semi-Supervised Clustering through the active learning method to improve the accuracy of the results. However,the algorithm may not be assigned to the current optimal problem during the sample assignment process. This paper proposes a method of assigning label samples to APCKmeans algorithm,and proposes an improved APCKmeans_I algorithm to achieve better clustering results with less supervisory information. The improved strategy is applied to PCKmeans(pairwise constrained K-means)algorithm,and PCKmeans_I algorithm is proposed. Experiments on the UCI reference data set show that the performance of the improved algorithm is obviously improved.

References:

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Last Update: 2018-06-30