A new exponential cluster validity index using Jaccard distance
Estimating the optimal number of clusters in an unsupervisedpartitioning of data sets has been a challenging area in recent years.These indices usually use two criteria called compactness andseparation to evaluate the efficiency of the performed clustering. Inthis paper a new separation measure for...
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| Format: | Article |
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Allameh Tabataba'i University Press
2012-12-01
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| Series: | Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī |
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| Online Access: | https://jims.atu.ac.ir/article_1901_acd6e2a0972280b8ccd5c5e7d1066c8d.pdf |
| _version_ | 1827392807623458816 |
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| author | Mohamad Hossein Fazel Zarandi Solmaz Ghazanfar Ahari Nader Ghaffari-Nasab |
| author_facet | Mohamad Hossein Fazel Zarandi Solmaz Ghazanfar Ahari Nader Ghaffari-Nasab |
| author_sort | Mohamad Hossein Fazel Zarandi |
| collection | DOAJ |
| description | Estimating the optimal number of clusters in an unsupervisedpartitioning of data sets has been a challenging area in recent years.These indices usually use two criteria called compactness andseparation to evaluate the efficiency of the performed clustering. Inthis paper a new separation measure for ECAS cluster validity index,proposed by Fazel et al. [1] is identified, which uses Jaccard distancein order to consider the whole shape of clusters. Jaccard distance usesthe size of intersection and union of fuzzy sets, giving the clustervalidity index more information about the overlap and separation ofclusters. This property results in high robustness of the proposed indexdealing with various degrees of fuzziness in comparison with ECAS.To test the efficiency of the proposed index in comparison with nineother indices existing in the literature, 15 data sets (3 existing datasetsand 12 artificial data sets) have been used. Computational resultsindicate robustness and high capability of the proposed index incomparison with previous indices |
| first_indexed | 2024-03-08T17:38:43Z |
| format | Article |
| id | doaj.art-2ef8031542f546c9bc84ea175ef85588 |
| institution | Directory Open Access Journal |
| issn | 2251-8029 2476-602X |
| language | fas |
| last_indexed | 2024-03-08T17:38:43Z |
| publishDate | 2012-12-01 |
| publisher | Allameh Tabataba'i University Press |
| record_format | Article |
| series | Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī |
| spelling | doaj.art-2ef8031542f546c9bc84ea175ef855882024-01-02T11:15:20ZfasAllameh Tabataba'i University PressMuṭāli̒āt-i Mudīriyyat-i Ṣan̒atī2251-80292476-602X2012-12-01102722431901A new exponential cluster validity index using Jaccard distanceMohamad Hossein Fazel Zarandi0Solmaz Ghazanfar Ahari1Nader Ghaffari-Nasab2استاد دانشکده مهندسی صنایع و سیستمهای مدیریت، دانشگاه صنعتی امیرکبیر، تهران، ایرانکارشناس ارشد مهندسی مالی دانشگاه صنعتی امیرکبیر، تهران، ایراندانشجوی دکتری مهندسی صنایع دانشگاه علم و صنعت ایران، تهران، ایران. )نویسنده مسئولEstimating the optimal number of clusters in an unsupervisedpartitioning of data sets has been a challenging area in recent years.These indices usually use two criteria called compactness andseparation to evaluate the efficiency of the performed clustering. Inthis paper a new separation measure for ECAS cluster validity index,proposed by Fazel et al. [1] is identified, which uses Jaccard distancein order to consider the whole shape of clusters. Jaccard distance usesthe size of intersection and union of fuzzy sets, giving the clustervalidity index more information about the overlap and separation ofclusters. This property results in high robustness of the proposed indexdealing with various degrees of fuzziness in comparison with ECAS.To test the efficiency of the proposed index in comparison with nineother indices existing in the literature, 15 data sets (3 existing datasetsand 12 artificial data sets) have been used. Computational resultsindicate robustness and high capability of the proposed index incomparison with previous indiceshttps://jims.atu.ac.ir/article_1901_acd6e2a0972280b8ccd5c5e7d1066c8d.pdfcluster validity indexjaccard distancefcmexponential compactness and separation |
| spellingShingle | Mohamad Hossein Fazel Zarandi Solmaz Ghazanfar Ahari Nader Ghaffari-Nasab A new exponential cluster validity index using Jaccard distance Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī cluster validity index jaccard distance fcm exponential compactness and separation |
| title | A new exponential cluster validity index using
Jaccard distance |
| title_full | A new exponential cluster validity index using
Jaccard distance |
| title_fullStr | A new exponential cluster validity index using
Jaccard distance |
| title_full_unstemmed | A new exponential cluster validity index using
Jaccard distance |
| title_short | A new exponential cluster validity index using
Jaccard distance |
| title_sort | new exponential cluster validity index using jaccard distance |
| topic | cluster validity index jaccard distance fcm exponential compactness and separation |
| url | https://jims.atu.ac.ir/article_1901_acd6e2a0972280b8ccd5c5e7d1066c8d.pdf |
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