{"id":"https://openalex.org/W3200924559","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533597","title":"Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison","display_name":"Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200924559","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533597","mag":"3200924559"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533597","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5009367143","display_name":"Arman Zharmagambetov","orcid":"https://orcid.org/0000-0002-2182-8291"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arman Zharmagambetov","raw_affiliation_strings":["University of California,Dept. of Computer Science and Engineering,Merced,CA,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Dept. of Computer Science and Engineering,Merced,CA,USA","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001414947","display_name":"Suryabhan Singh Hada","orcid":"https://orcid.org/0000-0001-5681-6832"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suryabhan Singh Hada","raw_affiliation_strings":["University of California,Dept. of Computer Science and Engineering,Merced,CA,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Dept. of Computer Science and Engineering,Merced,CA,USA","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024657565","display_name":"Magzhan Gabidolla","orcid":null},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Magzhan Gabidolla","raw_affiliation_strings":["University of California,Dept. of Computer Science and Engineering,Merced,CA,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Dept. of Computer Science and Engineering,Merced,CA,USA","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057957982","display_name":"Miguel \u00c1. Carreira-Perpi\u00f1\u00e1n","orcid":"https://orcid.org/0000-0003-3297-9375"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Miguel A. Carreira-Perpinan","raw_affiliation_strings":["University of California,Dept. of Computer Science and Engineering,Merced,CA,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Dept. of Computer Science and Engineering,Merced,CA,USA","institution_ids":["https://openalex.org/I156087764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009367143"],"corresponding_institution_ids":["https://openalex.org/I156087764"],"apc_list":null,"apc_paid":null,"fwci":2.4474,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.90914028,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9983999729156494,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9983999729156494,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.996399998664856,"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/T10320","display_name":"Neural Networks and Applications","score":0.992900013923645,"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":0.6710387468338013},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6624917984008789},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.6309225559234619},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.563459575176239},{"id":"https://openalex.org/keywords/oblique-case","display_name":"Oblique case","score":0.5575326681137085},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5445937514305115},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5154362916946411},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4820752739906311},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.442121297121048},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.43374839425086975},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37323665618896484},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33227699995040894},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2820766568183899},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07883840799331665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6710387468338013},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6624917984008789},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.6309225559234619},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.563459575176239},{"id":"https://openalex.org/C160697094","wikidata":"https://www.wikidata.org/wiki/Q1233197","display_name":"Oblique case","level":2,"score":0.5575326681137085},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5445937514305115},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5154362916946411},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4820752739906311},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.442121297121048},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.43374839425086975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37323665618896484},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33227699995040894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2820766568183899},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07883840799331665},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533597","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6800000071525574,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1671049838","display_name":null,"funder_award_id":"IIS-2007147","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W23988625","https://openalex.org/W1480376833","https://openalex.org/W1504694836","https://openalex.org/W1519043595","https://openalex.org/W1594031697","https://openalex.org/W1780185704","https://openalex.org/W1833744030","https://openalex.org/W1896739462","https://openalex.org/W1970074386","https://openalex.org/W2029606207","https://openalex.org/W2101234009","https://openalex.org/W2112796928","https://openalex.org/W2118585731","https://openalex.org/W2125055259","https://openalex.org/W2142334564","https://openalex.org/W2149421006","https://openalex.org/W2161349318","https://openalex.org/W2179503016","https://openalex.org/W2604736517","https://openalex.org/W2787894218","https://openalex.org/W2891895300","https://openalex.org/W2986976431","https://openalex.org/W3035329113","https://openalex.org/W3035751413","https://openalex.org/W3043221510","https://openalex.org/W3093489024","https://openalex.org/W3101760475","https://openalex.org/W3120740533","https://openalex.org/W3163041779","https://openalex.org/W3199696482","https://openalex.org/W4285719527","https://openalex.org/W4297673529","https://openalex.org/W4399570248","https://openalex.org/W6675354045","https://openalex.org/W6677656871","https://openalex.org/W6685719144","https://openalex.org/W6769510447","https://openalex.org/W6779842540","https://openalex.org/W6779920328","https://openalex.org/W6795421910","https://openalex.org/W6801383752","https://openalex.org/W6869422906"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2385104873"],"abstract_inverted_index":{"Learning":[0],"decision":[1,152],"trees":[2,29,108,123],"is":[3],"a":[4,12,32,65,117,144],"difficult":[5],"optimization":[6,44,95],"problem:":[7],"nonconvex,":[8],"nondifferentiable":[9],"and":[10,57,69,78,102,105,140],"over":[11,87],"huge":[13],"number":[14],"of":[15,62,67,74,151],"tree":[16,79,93],"structures.":[17],"The":[18,81],"dominant":[19],"paradigm":[20,147],"in":[21,24,64,72,128,146,148],"practice,":[22],"established":[23],"the":[25,53],"1980s,":[26],"are":[27,133],"axis-aligned":[28,104,126],"trained":[30],"with":[31,90],"greedy":[33],"recursive":[34],"partitioning":[35],"algorithm":[36],"such":[37],"as":[38],"CART":[39,88],"or":[40],"C5.0.":[41],"Several":[42],"non-greedy":[43,82],"algorithms":[45,83],"have":[46],"been":[47],"proposed":[48],"recently,":[49],"which":[50],"optimize":[51],"all":[52,112],"nodes'":[54],"parameters":[55],"jointly,":[56],"we":[58],"compare":[59],"experimentally":[60],"some":[61],"them":[63],"range":[66],"classification":[68],"regression":[70],"datasets,":[71],"terms":[73],"accuracy,":[75],"training":[76],"time":[77],"size.":[80],"do":[84],"not":[85],"improve":[86],"significantly":[89],"one":[91],"exception,":[92],"alternating":[94],"(TAO).":[96],"TAO":[97,120],"scales":[98],"to":[99,125],"large":[100,118],"datasets":[101],"produces":[103],"especially":[106],"oblique":[107,122],"that":[109],"consistently":[110],"outperform":[111],"other":[113],"algorithms,":[114],"often":[115],"by":[116],"margin.":[119],"makes":[121],"preferable":[124],"ones":[127],"many":[129],"cases,":[130],"since":[131],"they":[132],"much":[134],"more":[135],"accurate":[136],"while":[137],"remaining":[138],"small":[139],"interpretable.":[141],"This":[142],"suggests":[143],"change":[145],"practical":[149],"applications":[150],"trees.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}