{"id":"https://openalex.org/W1533026269","doi":"https://doi.org/10.1109/ijcnn.2005.1555984","title":"Effective neural network pruning using cross-validation","display_name":"Effective neural network pruning using cross-validation","publication_year":2006,"publication_date":"2006-01-05","ids":{"openalex":"https://openalex.org/W1533026269","doi":"https://doi.org/10.1109/ijcnn.2005.1555984","mag":"1533026269"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2005.1555984","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555984","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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/A5113653299","display_name":"Thuan Quang Huynh","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"T.Q. Huynh","raw_affiliation_strings":["School of Computing, National University of Singapore, Singapore","Sch. of Comput., National Univ. of Singapore, Singapore#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Sch. of Comput., National Univ. of Singapore, Singapore#TAB#","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067016419","display_name":"Rudy Setiono","orcid":"https://orcid.org/0000-0003-2708-7727"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"R. Setiono","raw_affiliation_strings":["School of Computing, National University of Singapore, Singapore","Sch. of Comput., National Univ. of Singapore, Singapore#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Sch. of Comput., National Univ. of Singapore, Singapore#TAB#","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5113653299"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":2.0396,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.85634198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2","issue":null,"first_page":"972","last_page":"977"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10057","display_name":"Face and Expression Recognition","score":0.9980999827384949,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9980999827384949,"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/pruning","display_name":"Pruning","score":0.8036302328109741},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7437868118286133},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7043696641921997},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6666828393936157},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.6341712474822998},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5627090334892273},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.542860209941864},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5307027697563171},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5281916856765747},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.47470417618751526},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.472166508436203},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4587010145187378},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.45761483907699585},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4474602937698364},{"id":"https://openalex.org/keywords/probabilistic-neural-network","display_name":"Probabilistic neural network","score":0.42245879769325256},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.4183274507522583},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16815263032913208}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8036302328109741},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7437868118286133},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7043696641921997},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6666828393936157},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.6341712474822998},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5627090334892273},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.542860209941864},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5307027697563171},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5281916856765747},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.47470417618751526},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.472166508436203},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4587010145187378},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.45761483907699585},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4474602937698364},{"id":"https://openalex.org/C134342201","wikidata":"https://www.wikidata.org/wiki/Q7246859","display_name":"Probabilistic neural network","level":4,"score":0.42245879769325256},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.4183274507522583},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16815263032913208},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2005.1555984","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555984","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/42824","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/42824","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W50076749","https://openalex.org/W1531870769","https://openalex.org/W1598333443","https://openalex.org/W2009784977","https://openalex.org/W2020663993","https://openalex.org/W2068484625","https://openalex.org/W2072605094","https://openalex.org/W2084812512","https://openalex.org/W2093190817","https://openalex.org/W2109779438","https://openalex.org/W2110179049","https://openalex.org/W2111719156","https://openalex.org/W2114766824","https://openalex.org/W2125055259","https://openalex.org/W2144513243","https://openalex.org/W6601962754","https://openalex.org/W6671611538","https://openalex.org/W6676553272","https://openalex.org/W6677103964","https://openalex.org/W6678449394","https://openalex.org/W6681151457"],"related_works":["https://openalex.org/W1595652908","https://openalex.org/W2375446027","https://openalex.org/W2067837718","https://openalex.org/W2179098615","https://openalex.org/W2089093251","https://openalex.org/W4385506173","https://openalex.org/W38478948","https://openalex.org/W4294967761","https://openalex.org/W2139532495","https://openalex.org/W2950022897"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,24,37,47,52,71,75,87,109],"problem":[4],"of":[5,26,36,54,74],"finding":[6],"neural":[7,114],"networks":[8],"with":[9],"optimal":[10],"topology":[11],"such":[12],"that":[13,51,57,108],"their":[14],"generalization":[15],"capability":[16],"is":[17,21,44,97],"maximized.":[18],"Our":[19,99],"approach":[20],"to":[22,46,92],"combine":[23],"use":[25],"a":[27,34,81],"penalty":[28,43],"function":[29,49],"during":[30],"network":[31,55,65,76,95,115],"training":[32,38],"and":[33,116],"subset":[35],"samples":[39,85],"for":[40,120],"cross-validation.":[41],"The":[42],"added":[45],"error":[48],"so":[50],"weights":[53],"connections":[56,66],"are":[58,90],"not":[59,78],"useful":[60],"have":[61],"small":[62],"magnitude.":[63],"Such":[64],"can":[67],"be":[68],"pruned":[69],"if":[70],"resulting":[72],"accuracy":[73],"does":[77],"change":[79],"beyond":[80],"preset":[82],"level.":[83],"Training":[84],"in":[86],"cross-validation":[88],"set":[89],"used":[91],"indicate":[93],"when":[94],"pruning":[96],"terminated.":[98],"results":[100],"on":[101],"32":[102],"publicly":[103],"available":[104],"data":[105],"sets":[106],"show":[107],"proposed":[110],"method":[111],"outperforms":[112],"existing":[113],"decision":[117],"tree":[118],"methods":[119],"classification.":[121]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
