|Table of Contents|

Research on Spectral Clustering Algorithm Based on Three-way Decision(PDF)

《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2018年03期
Page:
6-
Research Field:
·人工智能算法与应用专栏·
Publishing date:

Info

Title:
Research on Spectral Clustering Algorithm Based on Three-way Decision
Author(s):
Shi Hong1Liu Qiang1Wang Pingxin12Yang Xibei1
(1.School of Computer,Jiangsu University of Science and Technology,Zhenjiang 212003,China)(2.College of Mathematics and Information Science,Hebei Normal University,Shijiazhuang 050024,China)
Keywords:
spectral clusteringthree-way decisionthree-way clusteringthree-way spectral clustering
PACS:
TP391
DOI:
10.3969/j.issn.1001-4616.2018.03.002
Abstract:
Hard clustering based on the assumption that a cluster must be represented by a set with crisp boundary. However,assigning uncertain points into a cluster will increase decision risk. Three-way clustering assigns the identified elements into the core region and the uncertain elements into the fringe region to reduce decision risk. In this paper,we present a new three-way spectral clustering by combining three-way decision and spectral clustering. In the proposed algorithm,we revise the process of spectral clustering and obtain an upper bound of each cluster. Perturbation analysis is applied to separate the core region from upper bound and the differences between upper bound and core region are regarded as the fringe region of specific cluster. The results on UCI data sets show that such strategy is effective in reducing the value of DBI and improving the values of ACC and AS.

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Last Update: 2018-11-19