{"id":"https://openalex.org/W4408847055","doi":"https://doi.org/10.1145/3725860","title":"A Performance Analysis of Lexicase-Based and Traditional Selection Methods in GP for Symbolic Regression","display_name":"A Performance Analysis of Lexicase-Based and Traditional Selection Methods in GP for Symbolic Regression","publication_year":2025,"publication_date":"2025-03-26","ids":{"openalex":"https://openalex.org/W4408847055","doi":"https://doi.org/10.1145/3725860"},"language":"en","primary_location":{"id":"doi:10.1145/3725860","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3725860","pdf_url":null,"source":{"id":"https://openalex.org/S4210221532","display_name":"ACM Transactions on Evolutionary Learning and Optimization","issn_l":"2688-299X","issn":["2688-299X","2688-3007"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Evolutionary Learning and Optimization","raw_type":"journal-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/A5004342649","display_name":"Alina Geiger","orcid":"https://orcid.org/0009-0002-3413-283X"},"institutions":[{"id":"https://openalex.org/I197323543","display_name":"Johannes Gutenberg University Mainz","ror":"https://ror.org/023b0x485","country_code":"DE","type":"education","lineage":["https://openalex.org/I197323543"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alina Geiger","raw_affiliation_strings":["Johannes Gutenberg University, Mainz, Germany","Johannes Gutenberg University Mainz, Germany"],"affiliations":[{"raw_affiliation_string":"Johannes Gutenberg University, Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]},{"raw_affiliation_string":"Johannes Gutenberg University Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066837192","display_name":"Dominik Sobania","orcid":"https://orcid.org/0000-0001-8873-7143"},"institutions":[{"id":"https://openalex.org/I197323543","display_name":"Johannes Gutenberg University Mainz","ror":"https://ror.org/023b0x485","country_code":"DE","type":"education","lineage":["https://openalex.org/I197323543"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dominik Sobania","raw_affiliation_strings":["Johannes Gutenberg University, Mainz, Germany","Johannes Gutenberg University Mainz, Germany"],"affiliations":[{"raw_affiliation_string":"Johannes Gutenberg University, Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]},{"raw_affiliation_string":"Johannes Gutenberg University Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035443886","display_name":"Franz Rothlauf","orcid":"https://orcid.org/0000-0003-3376-427X"},"institutions":[{"id":"https://openalex.org/I197323543","display_name":"Johannes Gutenberg University Mainz","ror":"https://ror.org/023b0x485","country_code":"DE","type":"education","lineage":["https://openalex.org/I197323543"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Franz Rothlauf","raw_affiliation_strings":["Johannes Gutenberg University, Mainz, Germany","Johannes Gutenberg University Mainz, Germany"],"affiliations":[{"raw_affiliation_string":"Johannes Gutenberg University, Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]},{"raw_affiliation_string":"Johannes Gutenberg University Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004342649"],"corresponding_institution_ids":["https://openalex.org/I197323543"],"apc_list":null,"apc_paid":null,"fwci":2.4849,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88787378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"6","issue":"1","first_page":"1","last_page":"40"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9994000196456909,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9994000196456909,"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/T10320","display_name":"Neural Networks and Applications","score":0.9580000042915344,"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":0.9519000053405762,"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/selection","display_name":"Selection (genetic algorithm)","score":0.6728655099868774},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5265541076660156},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.49799084663391113},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4714568257331848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4686899483203888},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46431729197502136},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35114747285842896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3436400294303894},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30800873041152954}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6728655099868774},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5265541076660156},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.49799084663391113},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4714568257331848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4686899483203888},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46431729197502136},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35114747285842896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3436400294303894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30800873041152954}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3725860","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3725860","pdf_url":null,"source":{"id":"https://openalex.org/S4210221532","display_name":"ACM Transactions on Evolutionary Learning and Optimization","issn_l":"2688-299X","issn":["2688-299X","2688-3007"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Evolutionary Learning and Optimization","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1551103807","https://openalex.org/W1969232932","https://openalex.org/W1978661986","https://openalex.org/W1982506807","https://openalex.org/W2034068348","https://openalex.org/W2054536516","https://openalex.org/W2072473332","https://openalex.org/W2100604298","https://openalex.org/W2484166844","https://openalex.org/W2561675875","https://openalex.org/W2798474464","https://openalex.org/W2852537662","https://openalex.org/W2945779572","https://openalex.org/W2961535796","https://openalex.org/W2997546679","https://openalex.org/W3004042307","https://openalex.org/W3004144506","https://openalex.org/W3046367554","https://openalex.org/W3103943707","https://openalex.org/W3176118284","https://openalex.org/W3184917773","https://openalex.org/W3206431085","https://openalex.org/W4212913914","https://openalex.org/W4220900977","https://openalex.org/W4285805321","https://openalex.org/W4285805493","https://openalex.org/W4293529798","https://openalex.org/W4366339690","https://openalex.org/W4377371972","https://openalex.org/W4379470176","https://openalex.org/W4384024946","https://openalex.org/W4385189557","https://openalex.org/W4400412639","https://openalex.org/W6604016310","https://openalex.org/W6646127818"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"In":[0,89],"recent":[1],"years,":[2],"several":[3],"new":[4],"lexicase-based":[5,66],"selection":[6,17,50,67,73,129,165],"variants":[7,26,46,149],"have":[8,39,54],"emerged":[9],"due":[10],"to":[11,41,91],"the":[12,63,98,141,161],"success":[13],"of":[14,34,58,85,152,163],"standard":[15],"lexicase":[16,49,148],"in":[18,75,117,130,171],"various":[19],"application":[20],"domains.":[21],"For":[22],"symbolic":[23,86],"regression":[24,87],"problems,":[25],"that":[27,47,121,160],"use":[28],"an":[29],"\\(\\epsilon\\)":[30,127],"-threshold":[31],"or":[32],"batches":[33,151],"training":[35,153],"cases,":[36],"among":[37],"others,":[38],"led":[40],"performance":[42],"improvements.":[43],"Lately,":[44],"especially":[45],"combine":[48],"and":[51],"down-sampling":[52,79,134,168],"strategies":[53,80],"received":[55],"a":[56,82,101,108,123,133],"lot":[57],"attention.":[59],"This":[60],"article":[61],"evaluates":[62],"most":[64,92],"relevant":[65],"methods":[68,74,99],"as":[69,71,112],"well":[70,170],"traditional":[72],"combination":[76,131,162],"with":[77,132,166],"different":[78],"on":[81],"wide":[83],"range":[84],"problems.":[88],"contrast":[90],"work,":[93],"we":[94,158],"not":[95],"only":[96],"compare":[97],"over":[100,107],"given":[102,109,124,142],"evaluation":[103,125],"budget,":[104,126],"but":[105],"also":[106],"time":[110,113,144],"budget":[111],"is":[114,145],"usually":[115],"limited":[116],"practice.":[118],"We":[119],"find":[120,159],"for":[122],"-lexicase":[128],"strategy":[135],"outperforms":[136],"all":[137,172],"other":[138],"methods.":[139],"If":[140],"running":[143],"very":[146],"short,":[147],"using":[150],"cases":[154],"perform":[155],"best.":[156],"Further,":[157],"tournament":[164],"informed":[167],"performs":[169],"studied":[173],"settings.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}