{"id":"https://openalex.org/W4410540293","doi":"https://doi.org/10.1007/s13042-025-02671-4","title":"Composite quantile regression with XGBoost using the novel arctan pinball loss","display_name":"Composite quantile regression with XGBoost using the novel arctan pinball loss","publication_year":2025,"publication_date":"2025-05-20","ids":{"openalex":"https://openalex.org/W4410540293","doi":"https://doi.org/10.1007/s13042-025-02671-4"},"language":"en","primary_location":{"id":"doi:10.1007/s13042-025-02671-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-025-02671-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-025-02671-4.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"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/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s13042-025-02671-4.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067098078","display_name":"Laurens Sluijterman","orcid":"https://orcid.org/0000-0001-6964-6481"},"institutions":[{"id":"https://openalex.org/I2802934949","display_name":"Radboud University Medical Center","ror":"https://ror.org/05wg1m734","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2802934949"]},{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Laurens Sluijterman","raw_affiliation_strings":["Department of Mathematics, Radboud University, Nijmegen, The Netherlands","Section Biostatistics, IQ Health, Radboud University Medical Center, Nijmegen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Radboud University, Nijmegen, The Netherlands","institution_ids":["https://openalex.org/I145872427"]},{"raw_affiliation_string":"Section Biostatistics, IQ Health, Radboud University Medical Center, Nijmegen, The Netherlands","institution_ids":["https://openalex.org/I145872427","https://openalex.org/I2802934949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068537947","display_name":"Frank Kreuwel","orcid":"https://orcid.org/0000-0003-3288-0893"},"institutions":[{"id":"https://openalex.org/I4210139739","display_name":"Vestas (Netherlands)","ror":"https://ror.org/04f0w3t91","country_code":"NL","type":"company","lineage":["https://openalex.org/I4210139739","https://openalex.org/I43275575"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Frank Kreuwel","raw_affiliation_strings":["System Operations, Alliander, Arnhem, The Netherlands"],"affiliations":[{"raw_affiliation_string":"System Operations, Alliander, Arnhem, The Netherlands","institution_ids":["https://openalex.org/I4210139739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013984637","display_name":"Eric Cator","orcid":"https://orcid.org/0000-0003-3873-7983"},"institutions":[{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Eric Cator","raw_affiliation_strings":["Department of Mathematics, Radboud University, Nijmegen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Radboud University, Nijmegen, The Netherlands","institution_ids":["https://openalex.org/I145872427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015444349","display_name":"Tom Heskes","orcid":"https://orcid.org/0000-0002-3398-5235"},"institutions":[{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Tom Heskes","raw_affiliation_strings":["Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands","institution_ids":["https://openalex.org/I145872427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067098078"],"corresponding_institution_ids":["https://openalex.org/I145872427","https://openalex.org/I2802934949"],"apc_list":{"value":2790,"currency":"EUR","value_usd":3590},"apc_paid":{"value":2790,"currency":"EUR","value_usd":3590},"fwci":5.8967,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.96210419,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"16","issue":"10","first_page":"7575","last_page":"7589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9609000086784363,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9538000226020813,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.69082111120224},{"id":"https://openalex.org/keywords/quantile-regression","display_name":"Quantile regression","score":0.629635214805603},{"id":"https://openalex.org/keywords/composite-number","display_name":"Composite number","score":0.5321411490440369},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4776943027973175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4562065303325653},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.45464619994163513},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3836548328399658},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3637007474899292},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35251933336257935},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.34122204780578613},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3249121904373169},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15715238451957703}],"concepts":[{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.69082111120224},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.629635214805603},{"id":"https://openalex.org/C104779481","wikidata":"https://www.wikidata.org/wiki/Q50707","display_name":"Composite number","level":2,"score":0.5321411490440369},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4776943027973175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4562065303325653},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.45464619994163513},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3836548328399658},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3637007474899292},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35251933336257935},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34122204780578613},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3249121904373169},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15715238451957703}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s13042-025-02671-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-025-02671-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-025-02671-4.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"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/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"},{"id":"pmh:oai:repository.ubn.ru.nl:2066/324960","is_oa":true,"landing_page_url":"https://hdl.handle.net/2066/324960","pdf_url":"https://repository.ubn.ru.nl//bitstream/handle/2066/324960/324960.pdf","source":{"id":"https://openalex.org/S4306401067","display_name":"Radboud Repository (Radboud University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I145872427","host_organization_name":"Radboud University Nijmegen","host_organization_lineage":["https://openalex.org/I145872427"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article / Letter to editor"}],"best_oa_location":{"id":"doi:10.1007/s13042-025-02671-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-025-02671-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-025-02671-4.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"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/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410540293.pdf","grobid_xml":"https://content.openalex.org/works/W4410540293.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1560021816","https://openalex.org/W1996742192","https://openalex.org/W2004803051","https://openalex.org/W2018851263","https://openalex.org/W2025720061","https://openalex.org/W2044449183","https://openalex.org/W2059053591","https://openalex.org/W2073545875","https://openalex.org/W2098824882","https://openalex.org/W2124934380","https://openalex.org/W2295598076","https://openalex.org/W2585908831","https://openalex.org/W2618521746","https://openalex.org/W2761736722","https://openalex.org/W2766900003","https://openalex.org/W2808779485","https://openalex.org/W2914888512","https://openalex.org/W2940010972","https://openalex.org/W2981792167","https://openalex.org/W3004732066","https://openalex.org/W3012981875","https://openalex.org/W3099697354","https://openalex.org/W3123890958","https://openalex.org/W3125188740","https://openalex.org/W3159897038","https://openalex.org/W3167433447","https://openalex.org/W3183312143","https://openalex.org/W4241653265","https://openalex.org/W4251244897","https://openalex.org/W6610114515"],"related_works":["https://openalex.org/W3125115104","https://openalex.org/W2468831641","https://openalex.org/W2945002008","https://openalex.org/W2625941561","https://openalex.org/W2365574773","https://openalex.org/W2988860017","https://openalex.org/W1557705136","https://openalex.org/W2131103914","https://openalex.org/W3043780870","https://openalex.org/W4399551708"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"paper":[2],"explores":[3],"the":[4,38,42,73,97,100,108,118,136,145],"use":[5,43,134],"of":[6,37,44,96,110,148],"XGBoost":[7,12],"for":[8,19],"composite":[9],"quantile":[10,86,160],"regression.":[11],"is":[13,105,152],"a":[14,33,48,70,93,123],"highly":[15],"popular":[16,56],"model":[17],"renowned":[18],"its":[20],"flexibility,":[21],"efficiency,":[22],"and":[23,81,155],"capability":[24],"to":[25,58,107,114,133],"deal":[26],"with":[27,47],"missing":[28],"data.":[29],"The":[30],"optimization":[31],"uses":[32,68],"second":[34,52,126,137],"order":[35,138],"approximation":[36,95],"loss":[39,45,71,121,142],"function,":[40,72],"complicating":[41],"functions":[46],"zero":[49],"or":[50],"vanishing":[51],"derivative.":[53],"Quantile":[54],"regression\u2014a":[55],"approach":[57],"obtain":[59],"conditional":[60],"quantiles":[61],"when":[62],"point":[63],"estimates":[64],"alone":[65],"are":[66,78],"insufficient\u2014unfortunately":[67],"such":[69],"pinball":[74,98,102,120],"loss.":[75],"Existing":[76],"workarounds":[77],"typically":[79],"inefficient":[80],"can":[82],"result":[83],"in":[84,135,157],"severe":[85],"crossings.":[87,161],"In":[88],"this":[89,141],"paper,":[90],"we":[91],"present":[92],"smooth":[94,116],"loss,":[99,103],"arctan":[101,119],"that":[104],"tailored":[106],"needs":[109],"XGBoost.":[111],"Specifically,":[112],"contrary":[113],"other":[115],"approximations,":[117],"has":[122],"relatively":[124],"large":[125],"derivative,":[127],"which":[128,151],"makes":[129],"it":[130],"more":[131,153],"suitable":[132],"approximation.":[139],"Using":[140],"function":[143],"enables":[144],"simultaneous":[146],"prediction":[147],"multiple":[149],"quantiles,":[150],"efficient":[154],"results":[156],"far":[158],"fewer":[159]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}