Loading…
Explaining Classification by Finding Response-Related Subgroups in Data
A method for explaining results of a regression based classifier is proposed. The data is clustered using a metric extracted from the classifier. This way, clusters found are related to classifier predictions, and each cluster can be considered a possible explanation for classification result. The c...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Conference Proceeding |
| Language: | English |
| Subjects: | |
| Online Access: | Request full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | |
|---|---|
| cites | |
| container_end_page | 75 |
| container_issue | |
| container_start_page | 69 |
| container_title | |
| container_volume | |
| creator | Parviainen, Elina Vehtari, Aki |
| description | A method for explaining results of a regression based classifier is proposed. The data is clustered using a metric extracted from the classifier. This way, clusters found are related to classifier predictions, and each cluster can be considered a possible explanation for classification result. The clusters are described by simple rules, meant to be easy for a human to understand. The key points of the work are presenting a modular framework for explaining the classification, and studying and comparing two different approaches for extracting a metric from a classifier model. |
| doi_str_mv | 10.1109/SNPD.2010.20 |
| format | conference_proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5521503</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5521503</ieee_id><sourcerecordid>5521503</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-275491f58d250126fc5c177aac81559c8f932862152628d2f0bfb1bb1c8a6ee33</originalsourceid><addsrcrecordid>eNpVjE1PwyAcxjFmiTp78-aFL9AJf6DA0XQvmixqtt0XoLBgKm1Gl7hvbxe9-Fye_PK8IPRAyYxSop-2bx_zGZARgVyhQktFOXAuOVB9_Y-hmqC7S1OTkdkNKnL-JKO4AFDyFq0W331rYorpgOvW5BxDdGaIXcL2jJcxNZdk43PfpezLjW_N4Bu8PdnDsTv1GceE52Yw92gSTJt98edTtFsudvVLuX5fvdbP6zJqMpQgBdc0CNWAIBSq4ISjUhrjFBVCOxU0A1UBFVDBWArEBkutpU6ZynvGpujx9zZ67_f9MX6Z43kvxLggjP0AkoNNuQ</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Explaining Classification by Finding Response-Related Subgroups in Data</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Parviainen, Elina ; Vehtari, Aki</creator><creatorcontrib>Parviainen, Elina ; Vehtari, Aki</creatorcontrib><description>A method for explaining results of a regression based classifier is proposed. The data is clustered using a metric extracted from the classifier. This way, clusters found are related to classifier predictions, and each cluster can be considered a possible explanation for classification result. The clusters are described by simple rules, meant to be easy for a human to understand. The key points of the work are presenting a modular framework for explaining the classification, and studying and comparing two different approaches for extracting a metric from a classifier model.</description><identifier>ISBN: 9781424474226</identifier><identifier>ISBN: 1424474221</identifier><identifier>EISBN: 9781424474219</identifier><identifier>EISBN: 1424474213</identifier><identifier>DOI: 10.1109/SNPD.2010.20</identifier><identifier>LCCN: 2010904473</identifier><language>eng</language><publisher>IEEE</publisher><subject>Biomedical computing ; Biomedical engineering ; Clustering algorithms ; Computer networks ; Concurrent computing ; data abstraction ; Data mining ; Distributed computing ; Input variables ; MLP classifier ; Predictive models ; Software engineering ; subgroup rules ; supervised clustering</subject><ispartof>2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2010, p.69-75</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5521503$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5521503$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Parviainen, Elina</creatorcontrib><creatorcontrib>Vehtari, Aki</creatorcontrib><title>Explaining Classification by Finding Response-Related Subgroups in Data</title><title>2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing</title><addtitle>SNPD</addtitle><description>A method for explaining results of a regression based classifier is proposed. The data is clustered using a metric extracted from the classifier. This way, clusters found are related to classifier predictions, and each cluster can be considered a possible explanation for classification result. The clusters are described by simple rules, meant to be easy for a human to understand. The key points of the work are presenting a modular framework for explaining the classification, and studying and comparing two different approaches for extracting a metric from a classifier model.</description><subject>Biomedical computing</subject><subject>Biomedical engineering</subject><subject>Clustering algorithms</subject><subject>Computer networks</subject><subject>Concurrent computing</subject><subject>data abstraction</subject><subject>Data mining</subject><subject>Distributed computing</subject><subject>Input variables</subject><subject>MLP classifier</subject><subject>Predictive models</subject><subject>Software engineering</subject><subject>subgroup rules</subject><subject>supervised clustering</subject><isbn>9781424474226</isbn><isbn>1424474221</isbn><isbn>9781424474219</isbn><isbn>1424474213</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpVjE1PwyAcxjFmiTp78-aFL9AJf6DA0XQvmixqtt0XoLBgKm1Gl7hvbxe9-Fye_PK8IPRAyYxSop-2bx_zGZARgVyhQktFOXAuOVB9_Y-hmqC7S1OTkdkNKnL-JKO4AFDyFq0W331rYorpgOvW5BxDdGaIXcL2jJcxNZdk43PfpezLjW_N4Bu8PdnDsTv1GceE52Yw92gSTJt98edTtFsudvVLuX5fvdbP6zJqMpQgBdc0CNWAIBSq4ISjUhrjFBVCOxU0A1UBFVDBWArEBkutpU6ZynvGpujx9zZ67_f9MX6Z43kvxLggjP0AkoNNuQ</recordid><startdate>201006</startdate><enddate>201006</enddate><creator>Parviainen, Elina</creator><creator>Vehtari, Aki</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201006</creationdate><title>Explaining Classification by Finding Response-Related Subgroups in Data</title><author>Parviainen, Elina ; Vehtari, Aki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-275491f58d250126fc5c177aac81559c8f932862152628d2f0bfb1bb1c8a6ee33</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Biomedical computing</topic><topic>Biomedical engineering</topic><topic>Clustering algorithms</topic><topic>Computer networks</topic><topic>Concurrent computing</topic><topic>data abstraction</topic><topic>Data mining</topic><topic>Distributed computing</topic><topic>Input variables</topic><topic>MLP classifier</topic><topic>Predictive models</topic><topic>Software engineering</topic><topic>subgroup rules</topic><topic>supervised clustering</topic><toplevel>online_resources</toplevel><creatorcontrib>Parviainen, Elina</creatorcontrib><creatorcontrib>Vehtari, Aki</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore (IEEE/IET Electronic Library - IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Parviainen, Elina</au><au>Vehtari, Aki</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Explaining Classification by Finding Response-Related Subgroups in Data</atitle><btitle>2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing</btitle><stitle>SNPD</stitle><date>2010-06</date><risdate>2010</risdate><spage>69</spage><epage>75</epage><pages>69-75</pages><isbn>9781424474226</isbn><isbn>1424474221</isbn><eisbn>9781424474219</eisbn><eisbn>1424474213</eisbn><abstract>A method for explaining results of a regression based classifier is proposed. The data is clustered using a metric extracted from the classifier. This way, clusters found are related to classifier predictions, and each cluster can be considered a possible explanation for classification result. The clusters are described by simple rules, meant to be easy for a human to understand. The key points of the work are presenting a modular framework for explaining the classification, and studying and comparing two different approaches for extracting a metric from a classifier model.</abstract><pub>IEEE</pub><doi>10.1109/SNPD.2010.20</doi><tpages>7</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISBN: 9781424474226 |
| ispartof | 2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2010, p.69-75 |
| issn | |
| language | eng |
| recordid | cdi_ieee_primary_5521503 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Biomedical computing Biomedical engineering Clustering algorithms Computer networks Concurrent computing data abstraction Data mining Distributed computing Input variables MLP classifier Predictive models Software engineering subgroup rules supervised clustering |
| title | Explaining Classification by Finding Response-Related Subgroups in Data |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-19T05%3A36%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Explaining%20Classification%20by%20Finding%20Response-Related%20Subgroups%20in%20Data&rft.btitle=2010%2011th%20ACIS%20International%20Conference%20on%20Software%20Engineering,%20Artificial%20Intelligence,%20Networking%20and%20Parallel/Distributed%20Computing&rft.au=Parviainen,%20Elina&rft.date=2010-06&rft.spage=69&rft.epage=75&rft.pages=69-75&rft.isbn=9781424474226&rft.isbn_list=1424474221&rft_id=info:doi/10.1109/SNPD.2010.20&rft.eisbn=9781424474219&rft.eisbn_list=1424474213&rft_dat=%3Cieee_6IE%3E5521503%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-275491f58d250126fc5c177aac81559c8f932862152628d2f0bfb1bb1c8a6ee33%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5521503&rfr_iscdi=true |