{"id":"https://openalex.org/W4295767818","doi":"https://doi.org/10.1109/fuzz-ieee55066.2022.9882604","title":"Increasing Accuracy and Explainability in Fuzzy Regression Trees: An Experimental Analysis","display_name":"Increasing Accuracy and Explainability in Fuzzy Regression Trees: An Experimental Analysis","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4295767818","doi":"https://doi.org/10.1109/fuzz-ieee55066.2022.9882604"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee55066.2022.9882604","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee55066.2022.9882604","pdf_url":null,"source":{"id":"https://openalex.org/S4363608205","display_name":"2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://zenodo.org/record/7376690","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007774813","display_name":"Alessio Bechini","orcid":"https://orcid.org/0000-0002-5951-1265"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Alessio Bechini","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy,56122"],"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy,56122","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001867305","display_name":"Jos\u00e9 Luis Corcuera B\u00e1rcena","orcid":"https://orcid.org/0000-0002-9984-1904"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Jose Luis Corcuera Barcena","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy,56122"],"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy,56122","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050435146","display_name":"Pietro Ducange","orcid":"https://orcid.org/0000-0003-4510-1350"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Pietro Ducange","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy,56122"],"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy,56122","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057031606","display_name":"Francesco Marcelloni","orcid":"https://orcid.org/0000-0002-5895-876X"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Marcelloni","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy,56122"],"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy,56122","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079169024","display_name":"Alessandro Renda","orcid":"https://orcid.org/0000-0002-0482-5048"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessandro Renda","raw_affiliation_strings":["University of Pisa,Department of Information Engineering,Pisa,Italy,56122"],"affiliations":[{"raw_affiliation_string":"University of Pisa,Department of Information Engineering,Pisa,Italy,56122","institution_ids":["https://openalex.org/I108290504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5007774813"],"corresponding_institution_ids":["https://openalex.org/I108290504"],"apc_list":null,"apc_paid":null,"fwci":0.6283,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67806223,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9987999796867371,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9983000159263611,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6539140343666077},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6033086776733398},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5875629782676697},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.5782037377357483},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5427354574203491},{"id":"https://openalex.org/keywords/fuzzy-inference","display_name":"Fuzzy inference","score":0.5175625681877136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5066633820533752},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.505690336227417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48337167501449585},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4282161295413971},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37759605050086975},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36523687839508057},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.33334383368492126},{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.322989821434021},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2566165626049042},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15051507949829102}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6539140343666077},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6033086776733398},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5875629782676697},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.5782037377357483},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5427354574203491},{"id":"https://openalex.org/C2986395286","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy inference","level":5,"score":0.5175625681877136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5066633820533752},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.505690336227417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48337167501449585},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4282161295413971},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37759605050086975},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36523687839508057},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.33334383368492126},{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.322989821434021},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2566165626049042},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15051507949829102},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/fuzz-ieee55066.2022.9882604","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee55066.2022.9882604","pdf_url":null,"source":{"id":"https://openalex.org/S4363608205","display_name":"2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},{"id":"pmh:oai:zenodo.org:7376690","is_oa":true,"landing_page_url":"https://zenodo.org/record/7376690","pdf_url":"https://zenodo.org/record/7376690","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"},{"id":"pmh:oai:arpi.unipi.it:11568/1141588","is_oa":false,"landing_page_url":"https://hdl.handle.net/11568/1141588","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:arts.units.it:11368/3120422","is_oa":false,"landing_page_url":"https://hdl.handle.net/11368/3120422","pdf_url":null,"source":{"id":"https://openalex.org/S4306400480","display_name":"ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142444530","host_organization_name":"University of Trieste","host_organization_lineage":["https://openalex.org/I142444530"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:7376690","is_oa":true,"landing_page_url":"https://zenodo.org/record/7376690","pdf_url":"https://zenodo.org/record/7376690","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"},"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4295767818.pdf","grobid_xml":"https://content.openalex.org/works/W4295767818.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W372068302","https://openalex.org/W826471991","https://openalex.org/W1594031697","https://openalex.org/W2002041997","https://openalex.org/W2016086965","https://openalex.org/W2118864451","https://openalex.org/W2122702721","https://openalex.org/W2123199310","https://openalex.org/W2158325524","https://openalex.org/W2182722412","https://openalex.org/W2565966100","https://openalex.org/W2904005914","https://openalex.org/W2981731882","https://openalex.org/W3000716014","https://openalex.org/W3082797190","https://openalex.org/W3110923481","https://openalex.org/W3189261151","https://openalex.org/W4206210655","https://openalex.org/W4213102919","https://openalex.org/W4242841269"],"related_works":["https://openalex.org/W2114654021","https://openalex.org/W2263529430","https://openalex.org/W2389800468","https://openalex.org/W4390103748","https://openalex.org/W2763641192","https://openalex.org/W2150377753","https://openalex.org/W2392430664","https://openalex.org/W3162202563","https://openalex.org/W2377425550","https://openalex.org/W2364727641"],"abstract_inverted_index":{"Regression":[0],"Trees":[1],"(RTs)":[2],"have":[3,30],"been":[4,81],"widely":[5],"used":[6,55],"in":[7,11,56,100,145],"the":[8,53,57,61,65,69,101,104,117,131,141,146,152],"last":[9],"decades":[10],"various":[12],"domains,":[13],"also":[14],"thanks":[15],"to":[16,32,113,119,136],"their":[17],"inherent":[18],"explainability.":[19,121],"Fuzzy":[20],"RTs":[21,24],"(FRTs)":[22],"extend":[23,87],"by":[25,95,129,161],"using":[26],"fuzzy":[27],"sets":[28],"and":[29,63,77,103,116,157],"proven":[31],"be":[33],"particularly":[34],"suitable":[35],"for":[36,59,93],"dealing":[37],"with":[38],"noisy":[39],"and/or":[40],"uncertain":[41],"environments.":[42],"The":[43,109,148],"modelling":[44],"capability":[45],"of":[46,71,140,164],"FRTs":[47,75,94],"depends,":[48],"among":[49],"other":[50],"factors,":[51],"on":[52,64,74],"model":[54],"leaves":[58,102],"determining":[60],"output,":[62],"inference":[66,107],"strategy.":[67,108],"Nevertheless,":[68],"impact":[70],"such":[72],"factors":[73],"accuracy":[76,156],"explainability":[78,158],"has":[79],"not":[80],"adequately":[82],"investigated.In":[83],"this":[84],"paper,":[85],"we":[86],"a":[88],"recently":[89],"proposed":[90],"learning":[91],"scheme":[92],"employing":[96,162],"both":[97,163],"linear":[98],"models":[99],"maximum":[105],"matching":[106],"former":[110],"extension":[111],"aims":[112],"increase":[114],"accuracy,":[115],"latter":[118],"improve":[120],"We":[122],"carried":[123],"out":[124],"an":[125],"extensive":[126],"experimental":[127],"analysis":[128],"comparing":[130],"four":[132],"FRT":[133],"versions":[134],"corresponding":[135],"any":[137],"possible":[138],"combination":[139],"two":[142],"extensions":[143],"introduced":[144],"paper.":[147],"results":[149],"show":[150],"that":[151],"best":[153],"trade-off":[154],"between":[155],"is":[159],"obtained":[160],"them.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}