{"id":"https://openalex.org/W3138033397","doi":"https://doi.org/10.1145/3442536.3442552","title":"Effective Tuning of Regression Models using an Evolutionary Approach: A Case Study","display_name":"Effective Tuning of Regression Models using an Evolutionary Approach: A Case Study","publication_year":2020,"publication_date":"2020-12-18","ids":{"openalex":"https://openalex.org/W3138033397","doi":"https://doi.org/10.1145/3442536.3442552","mag":"3138033397"},"language":"en","primary_location":{"id":"doi:10.1145/3442536.3442552","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442536.3442552","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3442536.3442552","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 3rd Artificial Intelligence and Cloud Computing Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3442536.3442552","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000564562","display_name":"S\u00e9amus Lankford","orcid":"https://orcid.org/0000-0003-1693-9533"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Seamus Lankford","raw_affiliation_strings":["Dublin City University, Ireland"],"affiliations":[{"raw_affiliation_string":"Dublin City University, Ireland","institution_ids":["https://openalex.org/I42934936"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5000564562"],"corresponding_institution_ids":["https://openalex.org/I42934936"],"apc_list":null,"apc_paid":null,"fwci":0.3977,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.706235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"102","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9990000128746033,"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":0.9990000128746033,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9922000169754028,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9825999736785889,"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/hyperparameter","display_name":"Hyperparameter","score":0.8896132707595825},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.8654006719589233},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7091637253761292},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6951978206634521},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.66605144739151},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6566769480705261},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.545450747013092},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5433687567710876},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.496310293674469},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.48855647444725037},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.48752114176750183},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.47136130928993225},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4637696146965027},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.416492760181427},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3586313724517822},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.19323867559432983},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15143603086471558},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12073856592178345}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8896132707595825},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.8654006719589233},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7091637253761292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6951978206634521},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.66605144739151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6566769480705261},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.545450747013092},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5433687567710876},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.496310293674469},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.48855647444725037},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.48752114176750183},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.47136130928993225},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4637696146965027},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.416492760181427},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3586313724517822},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.19323867559432983},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15143603086471558},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12073856592178345},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3442536.3442552","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442536.3442552","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3442536.3442552","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 3rd Artificial Intelligence and Cloud Computing Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:doras.dcu.ie:28349","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401511","display_name":"Dublin City University Open Access Institutional Repository (Dublin City University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I42934936","host_organization_name":"Dublin City University","host_organization_lineage":["https://openalex.org/I42934936"],"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"}],"best_oa_location":{"id":"doi:10.1145/3442536.3442552","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442536.3442552","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3442536.3442552","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 3rd Artificial Intelligence and Cloud Computing Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3138033397.pdf","grobid_xml":"https://content.openalex.org/works/W3138033397.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W2055196576","https://openalex.org/W2775233965","https://openalex.org/W2905185626","https://openalex.org/W2964024268","https://openalex.org/W2998993395","https://openalex.org/W3004290819","https://openalex.org/W4205471372","https://openalex.org/W4292872700"],"related_works":["https://openalex.org/W2953665647","https://openalex.org/W4281646320","https://openalex.org/W4205712847","https://openalex.org/W3169687406","https://openalex.org/W4388119537","https://openalex.org/W3014750173","https://openalex.org/W3114025147","https://openalex.org/W4287818966","https://openalex.org/W3192751261","https://openalex.org/W3200811867"],"abstract_inverted_index":{"Hyperparameters":[0],"enable":[1],"machine":[2,21],"learning":[3,22],"algorithms":[4,90],"to":[5,93,132],"be":[6,133],"customized":[7],"for":[8,30,56,113],"specific":[9],"datasets.":[10],"Choosing":[11],"the":[12,85,110,119,126],"right":[13],"hyperparameters":[14,29],"is":[15,100,130],"a":[16,45,114,148],"challenge":[17],"often":[18],"faced":[19],"by":[20],"practitioners.":[23],"With":[24],"this":[25,97],"research,":[26],"tuning":[27,70],"of":[28,48,64,84,137,150],"regression":[31,49,115],"models":[32],"was":[33],"explored.":[34],"Models":[35],"predicting":[36],"house":[37],"prices":[38],"in":[39],"King":[40,120],"County":[41,121],"were":[42,60,79,91],"created":[43],"using":[44,71],"detailed":[46],"suite":[47],"algorithms.":[50],"Traditional":[51],"approaches,":[52],"and":[53,68,76,128],"evolutionary":[54,89,104],"algorithms,":[55],"improving":[57],"model":[58,94,116,139],"accuracy":[59,112],"evaluated.":[61],"A":[62],"variety":[63,149],"feature":[65,143,151],"selection":[66,144,152],"methods":[67,153],"hyperparameter":[69],"grid":[72],"search,":[73],"random":[74],"search":[75],"pipeline":[77],"optimization":[78],"also":[80],"studied":[81],"as":[82],"part":[83],"traditional":[86],"approaches.":[87],"Furthermore,":[88],"applied":[92],"optimization.":[95],"In":[96],"paper,":[98],"it":[99],"shown":[101,131],"that":[102],"an":[103,134],"approach,":[105],"implemented":[106],"with":[107],"TPOT,":[108],"achieves":[109],"highest":[111],"based":[117],"on":[118],"dataset.":[122],"Regarding":[123],"metrics,":[124],"combining":[125],"RMSE":[127],"metrics":[129],"effective":[135],"means":[136],"determining":[138],"accuracy.":[140],"Finally,":[141],"greedy":[142],"performed":[145],"best":[146],"when":[147],"are":[154],"compared.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}