{"id":"https://openalex.org/W2895900397","doi":"https://doi.org/10.1109/fuzz-ieee.2018.8491540","title":"Fuzzy and Possibilistic Clustering for Multiple Instance Linear Regression","display_name":"Fuzzy and Possibilistic Clustering for Multiple Instance Linear Regression","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2895900397","doi":"https://doi.org/10.1109/fuzz-ieee.2018.8491540","mag":"2895900397"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2018.8491540","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2018.8491540","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088517406","display_name":"Mohamed Trabelsi","orcid":"https://orcid.org/0000-0001-5841-5012"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohamed Trabelsi","raw_affiliation_strings":["Multimedia Research Lab, CECS Dept., University of Louisville"],"affiliations":[{"raw_affiliation_string":"Multimedia Research Lab, CECS Dept., University of Louisville","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044691751","display_name":"Hichem Frigui","orcid":"https://orcid.org/0000-0002-8281-1629"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hichem Frigui","raw_affiliation_strings":["Multimedia Research Lab, CECS Dept., University of Louisville"],"affiliations":[{"raw_affiliation_string":"Multimedia Research Lab, CECS Dept., University of Louisville","institution_ids":["https://openalex.org/I142740786"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088517406"],"corresponding_institution_ids":["https://openalex.org/I142740786"],"apc_list":null,"apc_paid":null,"fwci":0.1045,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45545531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"33","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9592999815940857,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7008692026138306},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6473091244697571},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6096460223197937},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5417078733444214},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5014102458953857},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4708299934864044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45454639196395874},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4452105760574341},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4304737150669098},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41952741146087646},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.410108745098114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36495769023895264},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13322985172271729}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7008692026138306},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6473091244697571},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6096460223197937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5417078733444214},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5014102458953857},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4708299934864044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45454639196395874},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4452105760574341},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4304737150669098},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41952741146087646},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.410108745098114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36495769023895264},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13322985172271729},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2018.8491540","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2018.8491540","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W181444816","https://openalex.org/W1535599202","https://openalex.org/W1550821944","https://openalex.org/W1929873255","https://openalex.org/W1965051455","https://openalex.org/W1984895402","https://openalex.org/W1989069564","https://openalex.org/W1989971192","https://openalex.org/W2002041442","https://openalex.org/W2076752034","https://openalex.org/W2078579128","https://openalex.org/W2098166271","https://openalex.org/W2105353986","https://openalex.org/W2108745803","https://openalex.org/W2110119381","https://openalex.org/W2110265366","https://openalex.org/W2113076747","https://openalex.org/W2113854955","https://openalex.org/W2117839624","https://openalex.org/W2118697091","https://openalex.org/W2120287764","https://openalex.org/W2120688485","https://openalex.org/W2127608660","https://openalex.org/W2135986560","https://openalex.org/W2149648623","https://openalex.org/W2154318594","https://openalex.org/W2978507805","https://openalex.org/W4244946557","https://openalex.org/W6633127331","https://openalex.org/W6640500741","https://openalex.org/W6669992580","https://openalex.org/W6676245398","https://openalex.org/W6677574362"],"related_works":["https://openalex.org/W2945382830","https://openalex.org/W4224807364","https://openalex.org/W2596632494","https://openalex.org/W2535986621","https://openalex.org/W1980197432","https://openalex.org/W2382432689","https://openalex.org/W2000612978","https://openalex.org/W4388110928","https://openalex.org/W1483228865","https://openalex.org/W4312412183"],"abstract_inverted_index":{"Multiple":[0],"instance":[1],"regression":[2,56,139],"(MIR)":[3],"operates":[4],"on":[5,145],"a":[6,55,64,90,146],"collection":[7],"of":[8,63,115,119,138,148],"bags,":[9],"where":[10],"each":[11,51,120,125],"bag":[12,52,121],"contains":[13],"multiple":[14,86,108],"instances":[15,34,49,104,118],"sharing":[16],"an":[17,73,81],"identical":[18],"real-valued":[19],"label.":[20,31],"Only":[21],"few":[22],"instances,":[23,26],"called":[24],"primary":[25,48,117],"contribute":[27],"to":[28,45,84,105,107,124,133],"the":[29,47,61,116,130,135],"bag's":[30],"The":[32,40],"remaining":[33],"are":[35,100],"noise":[36],"and":[37,53],"outliers":[38],"observations.":[39],"goal":[41],"in":[42,102],"MIR":[43],"is":[44],"identify":[46,134],"within":[50],"learn":[54,85],"model":[57],"that":[58,75,97,154],"can":[59],"predict":[60],"label":[62],"previously":[65],"unseen":[66],"bag.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"present":[72],"algorithm":[74],"uses":[76],"robust":[77],"fuzzy":[78,98],"clustering":[79],"with":[80,122],"appropriate":[82],"distance":[83],"linear":[87],"models":[88],"from":[89],"noisy":[91],"feature":[92],"space":[93],"simultaneously.":[94],"We":[95,127,141,152],"show":[96,153],"memberships":[99,112,132],"useful":[101],"allowing":[103],"belong":[106],"models,":[109],"while":[110],"possibilistic":[111,131],"allow":[113],"identification":[114],"respect":[123],"model.":[126],"also":[128],"use":[129],"optimal":[136],"number":[137],"models.":[140],"evaluate":[142],"our":[143,155],"approach":[144,156],"series":[147],"synthetic":[149],"data":[150],"sets.":[151],"achieves":[157],"higher":[158],"accuracy":[159],"than":[160],"existing":[161],"methods.":[162]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}