{"id":"https://openalex.org/W4324325338","doi":"https://doi.org/10.1007/s10618-023-00921-z","title":"Joint leaf-refinement and ensemble pruning through $$L_1$$ regularization","display_name":"Joint leaf-refinement and ensemble pruning through $$L_1$$ regularization","publication_year":2023,"publication_date":"2023-03-15","ids":{"openalex":"https://openalex.org/W4324325338","doi":"https://doi.org/10.1007/s10618-023-00921-z"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-023-00921-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-023-00921-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-023-00921-z.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058070822","display_name":"Sebastian Buschj\u00e4ger","orcid":"https://orcid.org/0000-0002-2780-3618"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Buschj\u00e4ger","raw_affiliation_strings":["Chair for Artificial Intelligence, TU Dortmund University, Otto-Hahn-Stra\u00dfe 12, 44221, Dortmund, NRW, Germany"],"affiliations":[{"raw_affiliation_string":"Chair for Artificial Intelligence, TU Dortmund University, Otto-Hahn-Stra\u00dfe 12, 44221, Dortmund, NRW, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065328227","display_name":"Katharina Morik","orcid":"https://orcid.org/0000-0003-1153-5986"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Katharina Morik","raw_affiliation_strings":["Chair for Artificial Intelligence, TU Dortmund University, Otto-Hahn-Stra\u00dfe 12, 44221, Dortmund, NRW, Germany"],"affiliations":[{"raw_affiliation_string":"Chair for Artificial Intelligence, TU Dortmund University, Otto-Hahn-Stra\u00dfe 12, 44221, Dortmund, NRW, Germany","institution_ids":["https://openalex.org/I200332995"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990,"provenance":"doaj"},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990,"provenance":"doaj"},"fwci":1.644,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":6,"citation_normalized_percentile":{"value":0.999956,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":94},"biblio":{"volume":"37","issue":"3","first_page":"1230","last_page":"1261"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9885,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9885,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9846,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9765,"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/regularization","display_name":"Regularization","score":0.695455},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.56254196}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.695455},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.63640696},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.56254196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.55825293},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5354187},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43245494},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4121216},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39271525},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08181974},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.054919124},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.050417393},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-023-00921-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-023-00921-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-023-00921-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-023-00921-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.57}],"grants":[{"funder":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft","award_id":"124020371"},{"funder":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung","award_id":"01|18038A"}],"datasets":[],"versions":[],"referenced_works_count":35,"referenced_works":["https://openalex.org/W1577983635","https://openalex.org/W1581797854","https://openalex.org/W1608733719","https://openalex.org/W1797580880","https://openalex.org/W1934570606","https://openalex.org/W1995276998","https://openalex.org/W2056132907","https://openalex.org/W2103346566","https://openalex.org/W2113242816","https://openalex.org/W2125555508","https://openalex.org/W2135046866","https://openalex.org/W2164726323","https://openalex.org/W2170872095","https://openalex.org/W2216946510","https://openalex.org/W2273278181","https://openalex.org/W2314383124","https://openalex.org/W2604868979","https://openalex.org/W2729784024","https://openalex.org/W2733186554","https://openalex.org/W2899500964","https://openalex.org/W2907415261","https://openalex.org/W2911964244","https://openalex.org/W2920071168","https://openalex.org/W2970867453","https://openalex.org/W2985361718","https://openalex.org/W3004543888","https://openalex.org/W3006236014","https://openalex.org/W3082623814","https://openalex.org/W4212883601","https://openalex.org/W4232478844","https://openalex.org/W4240247968","https://openalex.org/W4244393449","https://openalex.org/W4289236186","https://openalex.org/W4297944103","https://openalex.org/W765477760"],"related_works":["https://openalex.org/W4206442282","https://openalex.org/W2594301978","https://openalex.org/W2395294869","https://openalex.org/W2384505857","https://openalex.org/W2379704676","https://openalex.org/W2378744544","https://openalex.org/W2373300491","https://openalex.org/W2073681303","https://openalex.org/W2051487156","https://openalex.org/W1998810860"],"abstract_inverted_index":{"Abstract":[0],"Ensembles":[1],"are":[2,58],"among":[3],"the":[4,12,23,26,30,76,83,86,96,105,109,113,151,164,185,204],"state-of-the-art":[5,186],"in":[6,22,108,209],"many":[7],"machine":[8],"learning":[9],"applications.":[10],"With":[11],"ongoing":[13],"integration":[14],"of":[15,25,28,35,56,85,98,112,206],"ML":[16],"models":[17,36,46],"into":[18,137,150],"everyday":[19],"life,":[20],"e.g.,":[21],"form":[24],"Internet":[27],"Things,":[29],"deployment":[31],"and":[32,39,52,80,160],"continuous":[33],"application":[34],"become":[37],"more":[38,40],"an":[41,168],"important":[42],"issue.":[43],"Therefore,":[44],"small":[45,54],"that":[47,74,94,133,174],"offer":[48],"good":[49],"predictive":[50,123],"performance":[51,84,97,183],"use":[53],"amounts":[55],"memory":[57],"required.":[59],"Ensemble":[60],"pruning":[61],"is":[62,91],"a":[63,71,92,99,130,138,190,200,210],"standard":[64],"technique":[65,93],"for":[66,117],"removing":[67],"unnecessary":[68],"classifiers":[69],"from":[70],"large":[72],"ensemble":[73,101],"reduces":[75],"overall":[77],"resource":[78],"consumption":[79],"sometimes":[81],"improves":[82,95],"original":[87],"ensemble.":[88],"Similarly,":[89],"leaf-refinement":[90,152],"tree":[100],"by":[102],"jointly":[103,158],"re-learning":[104],"probability":[106],"estimates":[107],"leaf":[110],"nodes":[111],"trees,":[114],"thereby":[115],"allowing":[116],"smaller":[118],"ensembles":[119],"while":[120],"preserving":[121],"their":[122],"performance.":[124],"In":[125,167],"this":[126],"paper,":[127],"we":[128,144,172],"develop":[129],"new":[131],"method":[132,208],"combines":[134],"both":[135],"approaches":[136],"single":[139],"algorithm.":[140],"To":[141],"do":[142],"so,":[143],"introduce":[145],"$$L_1$$":[146],"L1":[148],"regularization":[149],"objective,":[153],"which":[154],"allows":[155],"us":[156],"to":[157],"prune":[159],"refine":[161],"trees":[162],"at":[163],"same":[165],"time.":[166],"extensive":[169],"experimental":[170,197],"evaluation,":[171],"show":[173],"our":[175,196,207],"approach":[176],"not":[177],"only":[178],"offers":[179,189],"statistically":[180],"significantly":[181],"better":[182,191],"than":[184],"but":[187],"also":[188],"accuracy-memory":[192],"trade-off.":[193],"We":[194],"conclude":[195],"evaluation":[198],"with":[199],"case":[201],"study":[202],"showing":[203],"effectiveness":[205],"real-world":[211],"setting.":[212]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4324325338","counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2024-12-08T23:19:27.681289","created_date":"2023-03-16"}