Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory

IEEE In evidential clustering, cluster-membership uncertainty is represented by Dempster-Shafer mass functions. The notion of evidential partition generalizes other soft clustering structures such as fuzzy, possibilistic or rough partitions. In this paper, we propose two extensions of the Rand index...

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Main Authors: Thierry Denoeux, Shoumei Li, Songsak Sriboonchitta
Format: Journal
Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/46655
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-466552018-04-25T07:23:23Z Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory Thierry Denoeux Shoumei Li Songsak Sriboonchitta Engineering Mathematics Agricultural and Biological Sciences IEEE In evidential clustering, cluster-membership uncertainty is represented by Dempster-Shafer mass functions. The notion of evidential partition generalizes other soft clustering structures such as fuzzy, possibilistic or rough partitions. In this paper, we propose two extensions of the Rand index for evaluating and comparing evidential partitions, called similarity and consistency indices. The similarity index is suitable for measuring the closeness of two soft partitions, while the consistency index allows one to assess the agreement, or lack of conflict, between a soft partition and the true hard partition. Simulation experiments illustrate some applications of these indices. 2018-04-25T06:59:03Z 2018-04-25T06:59:03Z 2017-06-21 Journal 10636706 2-s2.0-85021814934 10.1109/TFUZZ.2017.2718484 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85021814934&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/46655
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Engineering
Mathematics
Agricultural and Biological Sciences
spellingShingle Engineering
Mathematics
Agricultural and Biological Sciences
Thierry Denoeux
Shoumei Li
Songsak Sriboonchitta
Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory
description IEEE In evidential clustering, cluster-membership uncertainty is represented by Dempster-Shafer mass functions. The notion of evidential partition generalizes other soft clustering structures such as fuzzy, possibilistic or rough partitions. In this paper, we propose two extensions of the Rand index for evaluating and comparing evidential partitions, called similarity and consistency indices. The similarity index is suitable for measuring the closeness of two soft partitions, while the consistency index allows one to assess the agreement, or lack of conflict, between a soft partition and the true hard partition. Simulation experiments illustrate some applications of these indices.
format Journal
author Thierry Denoeux
Shoumei Li
Songsak Sriboonchitta
author_facet Thierry Denoeux
Shoumei Li
Songsak Sriboonchitta
author_sort Thierry Denoeux
title Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory
title_short Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory
title_full Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory
title_fullStr Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory
title_full_unstemmed Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory
title_sort evaluating and comparing soft partitions: an approach based on dempster-shafer theory
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85021814934&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/46655
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