Assessing the quality of fuzzy partitions using relative intersection
DC Field | Value | Language |
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dc.contributor.author | Kim, Dae-Won | - |
dc.contributor.author | Kim, Y.I. | - |
dc.contributor.author | Lee, D. | - |
dc.contributor.author | Lee, K.H. | - |
dc.date.available | 2020-06-16T02:21:30Z | - |
dc.date.issued | 2005-03 | - |
dc.identifier.issn | 0916-8532 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/40664 | - |
dc.description.abstract | In this paper, conventional validity indexes are reviewed and the shortcomings of the fuzzy cluster validation index based on intercluster proximity are examined. Based on these considerations, a new cluster validity index is proposed for fuzzy partitions obtained from the fuzzy c-means algorithm. The proposed validity index is defined as the average value of the relative intersections of all possible pairs of fuzzy clusters in the system. It computes the overlap between two fuzzy clusters by considering the intersection of each data point in the overlap. The optimal number of clusters is obtained by minimizing the validity index with respect to c. Experiments in which the proposed validity index and several conventional validity indexes were applied to well known data sets highlight the superior qualities of the proposed index. | - |
dc.format.extent | 9 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG | - |
dc.title | Assessing the quality of fuzzy partitions using relative intersection | - |
dc.type | Article | - |
dc.identifier.doi | 10.1093/ietisy/e88-d.3.594 | - |
dc.identifier.bibliographicCitation | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E88D, no.3, pp 594 - 602 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000227828100031 | - |
dc.identifier.scopusid | 2-s2.0-24144452881 | - |
dc.citation.endPage | 602 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 594 | - |
dc.citation.title | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | - |
dc.citation.volume | E88D | - |
dc.type.docType | Article | - |
dc.publisher.location | 일본 | - |
dc.subject.keywordAuthor | cluster validity | - |
dc.subject.keywordAuthor | fuzzy clustering | - |
dc.subject.keywordAuthor | fuzzy c-means | - |
dc.subject.keywordPlus | CLUSTER VALIDITY | - |
dc.subject.keywordPlus | INDEX | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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