{"id":"https://openalex.org/W2811348585","doi":"https://doi.org/10.1109/icmlc.2018.8527063","title":"J-Measure Based Pruning for Advancing Classification Performance of Information Entropy Based Rule Generation","display_name":"J-Measure Based Pruning for Advancing Classification Performance of Information Entropy Based Rule Generation","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2811348585","doi":"https://doi.org/10.1109/icmlc.2018.8527063","mag":"2811348585"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2018.8527063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2018.8527063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100349055","display_name":"Han Liu","orcid":"https://orcid.org/0000-0002-7731-8258"},"institutions":[{"id":"https://openalex.org/I79510175","display_name":"Cardiff University","ror":"https://ror.org/03kk7td41","country_code":"GB","type":"education","lineage":["https://openalex.org/I79510175"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Han Liu","raw_affiliation_strings":["School of Computer Science and Informatics, Cardiff University Queen\u2019s Buildings 5 The Parade, Cardiff, United Kingdom","School of Computer Science and Informatics, Cardiff University Queen's Buildings 5 The Parade, Cardiff, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Informatics, Cardiff University Queen\u2019s Buildings 5 The Parade, Cardiff, United Kingdom","institution_ids":["https://openalex.org/I79510175"]},{"raw_affiliation_string":"School of Computer Science and Informatics, Cardiff University Queen's Buildings 5 The Parade, Cardiff, United Kingdom","institution_ids":["https://openalex.org/I79510175"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109060474","display_name":"Mihaela Cocea","orcid":null},"institutions":[{"id":"https://openalex.org/I63072094","display_name":"University of Portsmouth","ror":"https://ror.org/03ykbk197","country_code":"GB","type":"education","lineage":["https://openalex.org/I63072094"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mihaela Cocea","raw_affiliation_strings":["School of computing, University of Portsmouth Buckingham Building, Lion Terrace, Portsmouth, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of computing, University of Portsmouth Buckingham Building, Lion Terrace, Portsmouth, United Kingdom","institution_ids":["https://openalex.org/I63072094"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073899636","display_name":"Weili Ding","orcid":"https://orcid.org/0000-0003-1671-7789"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weili Ding","raw_affiliation_strings":["Laboratory of Pattern Recognition and Intelligent Systems Key Laboratory of Industrial Computer Control Engineering of Heibei Provience, Yanshan University, Qinghuangdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Pattern Recognition and Intelligent Systems Key Laboratory of Industrial Computer Control Engineering of Heibei Provience, Yanshan University, Qinghuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"7414","issue":null,"first_page":"485","last_page":"490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9922999739646912,"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/overfitting","display_name":"Overfitting","score":0.9080216884613037},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7978467345237732},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7478469014167786},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6902068257331848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6634455919265747},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6435577273368835},{"id":"https://openalex.org/keywords/divide-and-conquer-algorithms","display_name":"Divide and conquer algorithms","score":0.6272910237312317},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5964200496673584},{"id":"https://openalex.org/keywords/incremental-decision-tree","display_name":"Incremental decision tree","score":0.41756671667099},{"id":"https://openalex.org/keywords/decision-tree-learning","display_name":"Decision tree learning","score":0.35852038860321045},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3353247046470642},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1785237193107605},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1729808747768402}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.9080216884613037},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7978467345237732},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7478469014167786},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6902068257331848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6634455919265747},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6435577273368835},{"id":"https://openalex.org/C71559656","wikidata":"https://www.wikidata.org/wiki/Q671298","display_name":"Divide and conquer algorithms","level":2,"score":0.6272910237312317},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5964200496673584},{"id":"https://openalex.org/C10229987","wikidata":"https://www.wikidata.org/wiki/Q17083028","display_name":"Incremental decision tree","level":4,"score":0.41756671667099},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.35852038860321045},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3353247046470642},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1785237193107605},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1729808747768402},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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":3,"locations":[{"id":"doi:10.1109/icmlc.2018.8527063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2018.8527063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"},{"id":"pmh:oai:https://orca.cardiff.ac.uk:111267","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401195","display_name":"ORCA Online Research @Cardiff (Cardiff University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79510175","host_organization_name":"Cardiff University","host_organization_lineage":["https://openalex.org/I79510175"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"pmh:oai:researchportal.port.ac.uk:publications/e7dee16e-9b77-4aff-8126-e89e2336f69f","is_oa":false,"landing_page_url":"https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000424","pdf_url":null,"source":{"id":"https://openalex.org/S4306401774","display_name":"Portsmouth Research Portal (University of Portsmouth)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63072094","host_organization_name":"University of Portsmouth","host_organization_lineage":["https://openalex.org/I63072094"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W52764945","https://openalex.org/W87999157","https://openalex.org/W1504694836","https://openalex.org/W1594031697","https://openalex.org/W1670263352","https://openalex.org/W1671614046","https://openalex.org/W1833977909","https://openalex.org/W1978515644","https://openalex.org/W2014709779","https://openalex.org/W2099321136","https://openalex.org/W2106476088","https://openalex.org/W2113090545","https://openalex.org/W2125055259","https://openalex.org/W2128420091","https://openalex.org/W2149706766","https://openalex.org/W2159047538","https://openalex.org/W2195636112","https://openalex.org/W2330820318","https://openalex.org/W2506439635","https://openalex.org/W2524374710","https://openalex.org/W2605204113","https://openalex.org/W2765192780","https://openalex.org/W2783377699","https://openalex.org/W2911964244","https://openalex.org/W3120740533","https://openalex.org/W4236137412","https://openalex.org/W4254239016","https://openalex.org/W4255271639","https://openalex.org/W6602174623","https://openalex.org/W6676864979","https://openalex.org/W6683229354"],"related_works":["https://openalex.org/W1585770001","https://openalex.org/W2075873371","https://openalex.org/W4245210885","https://openalex.org/W84383711","https://openalex.org/W4242351093","https://openalex.org/W2030894524","https://openalex.org/W1982169401","https://openalex.org/W1648970942","https://openalex.org/W2811372817","https://openalex.org/W2120748120"],"abstract_inverted_index":{"Learning":[0],"of":[1,8,32,49,73,92,120,160,167,186],"classification":[2],"rules":[3,28,41],"is":[4,24,105,114,138,176],"a":[5,33,99],"popular":[6],"approach":[7],"machine":[9],"learning,":[10,64],"which":[11,82,104],"can":[12,69,144],"be":[13],"achieved":[14],"through":[15],"two":[16,53],"strategies,":[17],"namely":[18],"divide-and-conquer":[19],"and":[20,62,132,172],"separate-and-conquer.":[21],"The":[22,110,154],"former":[23],"aimed":[25],"at":[26],"generating":[27],"in":[29],"the":[30,37,51,118,121,130,147,158,165,168,173,184],"form":[31],"decision":[34,59],"tree,":[35],"whereas":[36],"latter":[38],"generates":[39],"if-then":[40],"directly":[42],"from":[43],"training":[44,80],"data.":[45],"From":[46],"this":[47,95],"point":[48],"view,":[50],"above":[52,148],"strategies":[54,68],"are":[55],"referred":[56,106],"to":[57,71,86,107,116,140,163],"as":[58,108],"tree":[60],"learning":[61,67,150,170],"rule":[63,75,125,149,169],"respectively.":[65],"Both":[66],"lead":[70],"production":[72],"complex":[74],"based":[76,101,124],"classifiers":[77],"that":[78,128,157],"overfit":[79],"data,":[81],"has":[83],"motivated":[84],"researchers":[85],"develop":[87],"pruning":[88,102,112],"algorithms":[89],"towards":[90],"reduction":[91],"overfitting.":[93,153],"In":[94],"paper,":[96],"we":[97],"propose":[98],"J-measure":[100],"algorithm,":[103],"Jmean-pruning.":[109],"proposed":[111],"algorithm":[113],"used":[115],"advance":[117,164],"performance":[119,166,175],"information":[122],"entropy":[123],"generation":[126],"method":[127,151,171],"follows":[129],"separate":[131],"conquer":[133],"strategy.":[134],"An":[135],"experimental":[136],"study":[137],"reported":[139],"show":[141,156],"how":[142],"Jmean-pruning":[143,161],"effectively":[145],"help":[146],"avoid":[152],"results":[155],"use":[159],"achieves":[162],"improved":[174],"very":[177],"comparable":[178],"or":[179],"even":[180],"considerably":[181],"better":[182],"than":[183],"one":[185],"C4.5.":[187]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}