A close‐up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation
The misclassification error distance and the adjusted Rand index are two of the most common criteria used to evaluate the performance of clustering algorithms. This paper provides an in‐depth comparison of the two criteria, with the aim of better understand exactly what they measure, their propertie...
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| Veröffentlicht in: | British journal of mathematical & statistical psychology 2021-05, Vol.74 (2), p.203-231 |
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| container_title | British journal of mathematical & statistical psychology |
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| creator | Chacón, José E. |
| description | The misclassification error distance and the adjusted Rand index are two of the most common criteria used to evaluate the performance of clustering algorithms. This paper provides an in‐depth comparison of the two criteria, with the aim of better understand exactly what they measure, their properties and their differences. Starting from their population origins, the investigation includes many data analysis examples and the study of particular cases in great detail. An exhaustive simulation study provides insight into the criteria distributions and reveals some previous misconceptions. |
| doi_str_mv | 10.1111/bmsp.12212 |
| format | Article |
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An exhaustive simulation study provides insight into the criteria distributions and reveals some previous misconceptions.</description><subject>adjusted Rand index</subject><subject>Algorithms</subject><subject>Classification</subject><subject>Clustering</subject><subject>confusion matrix</subject><subject>Criteria</subject><subject>Data analysis</subject><subject>external clustering evaluation</subject><subject>misclassification error distance</subject><subject>Performance evaluation</subject><issn>0007-1102</issn><issn>2044-8317</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp90cFO3DAQBmALtYItcOEBkCUuqFKox07i5EhRSytRFQH3yGuPW6-SOLWTAhfUR-gz8iQ4u9ADh_oykufTb1k_IQfATiCdD8suDifAOfAtsuAsz7NKgHxDFowxmQEwvkPexbhiDHjBym2yIwSrWQHVgjycUt36iI9__k4D1b4bVHDR99RbOv5E2rmoWxWjs06r0aUFhuADNS6OqtdIVW_WUJnVFEc09Gq-cb3BO2oTxLsRQ6_a9My8D67_QfG3aqd12h55a1Ubcf957pKbz59uzr5kF9_Pv56dXmRaFJJnRtXVUoKx5RLyskat0qiQVWVpuZQacoOIAiqphZC6qtEYaZUpc7RKCbFLjjexQ_C_JoxjM_8L21b16KfY8LwQZVUXvE706BVd-Wn-QFIFgMwlL4uk3m-UDj7GgLYZgutUuG-ANXMpzVxKsy4l4cPnyGnZoflHX1pIADbg1rV4_5-o5uO368tN6BPJM5ph</recordid><startdate>202105</startdate><enddate>202105</enddate><creator>Chacón, José E.</creator><general>British Psychological Society</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope><scope>K9.</scope><scope>7X8</scope></search><sort><creationdate>202105</creationdate><title>A close‐up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation</title><author>Chacón, José E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3572-da98b71df6b1469eca1468e0866f277c14deee3187c337c89edd7fad64efaa33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>adjusted Rand index</topic><topic>Algorithms</topic><topic>Classification</topic><topic>Clustering</topic><topic>confusion matrix</topic><topic>Criteria</topic><topic>Data analysis</topic><topic>external clustering evaluation</topic><topic>misclassification error distance</topic><topic>Performance evaluation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chacón, José E.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>British journal of mathematical & statistical psychology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chacón, José E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A close‐up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation</atitle><jtitle>British journal of mathematical & statistical psychology</jtitle><addtitle>Br J Math Stat Psychol</addtitle><date>2021-05</date><risdate>2021</risdate><volume>74</volume><issue>2</issue><spage>203</spage><epage>231</epage><pages>203-231</pages><issn>0007-1102</issn><eissn>2044-8317</eissn><abstract>The misclassification error distance and the adjusted Rand index are two of the most common criteria used to evaluate the performance of clustering algorithms. This paper provides an in‐depth comparison of the two criteria, with the aim of better understand exactly what they measure, their properties and their differences. Starting from their population origins, the investigation includes many data analysis examples and the study of particular cases in great detail. An exhaustive simulation study provides insight into the criteria distributions and reveals some previous misconceptions.</abstract><cop>England</cop><pub>British Psychological Society</pub><pmid>33090518</pmid><doi>10.1111/bmsp.12212</doi><tpages>29</tpages></addata></record> |
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| language | eng |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | adjusted Rand index Algorithms Classification Clustering confusion matrix Criteria Data analysis external clustering evaluation misclassification error distance Performance evaluation |
| title | A close‐up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation |
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