{"id":"https://openalex.org/W1621275771","doi":"https://doi.org/10.1109/ijcnn.2015.7280763","title":"Efficient conformal regressors using bagged neural nets","display_name":"Efficient conformal regressors using bagged neural nets","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1621275771","doi":"https://doi.org/10.1109/ijcnn.2015.7280763","mag":"1621275771"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2015.7280763","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280763","pdf_url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7280763","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7280763","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103036745","display_name":"Ulf Johansson","orcid":"https://orcid.org/0000-0003-0412-6199"},"institutions":[{"id":"https://openalex.org/I1323252656","display_name":"Information Technology University","ror":"https://ror.org/00ngv8j44","country_code":"PK","type":"education","lineage":["https://openalex.org/I1323252656"]},{"id":"https://openalex.org/I992397","display_name":"University of Bor\u00e5s","ror":"https://ror.org/01fdxwh83","country_code":"SE","type":"education","lineage":["https://openalex.org/I992397"]}],"countries":["PK","SE"],"is_corresponding":true,"raw_author_name":"Ulf Johansson","raw_affiliation_strings":["Department of Information Technology, University of Bor\u00e5s, Sweden","[Dept. of Information Technology, University of Bor\u00e5s, Sweden]"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, University of Bor\u00e5s, Sweden","institution_ids":["https://openalex.org/I992397"]},{"raw_affiliation_string":"[Dept. of Information Technology, University of Bor\u00e5s, Sweden]","institution_ids":["https://openalex.org/I1323252656"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072426290","display_name":"Cecilia S\u00f6nstr\u00f6d","orcid":"https://orcid.org/0009-0009-0404-2586"},"institutions":[{"id":"https://openalex.org/I992397","display_name":"University of Bor\u00e5s","ror":"https://ror.org/01fdxwh83","country_code":"SE","type":"education","lineage":["https://openalex.org/I992397"]},{"id":"https://openalex.org/I1323252656","display_name":"Information Technology University","ror":"https://ror.org/00ngv8j44","country_code":"PK","type":"education","lineage":["https://openalex.org/I1323252656"]}],"countries":["PK","SE"],"is_corresponding":false,"raw_author_name":"Cecilia Sonstrod","raw_affiliation_strings":["Department of Information Technology, University of Bor\u00e5s, Sweden","[Dept. of Information Technology, University of Bor\u00e5s, Sweden]"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, University of Bor\u00e5s, Sweden","institution_ids":["https://openalex.org/I992397"]},{"raw_affiliation_string":"[Dept. of Information Technology, University of Bor\u00e5s, Sweden]","institution_ids":["https://openalex.org/I1323252656"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059387263","display_name":"Henrik Linusson","orcid":null},"institutions":[{"id":"https://openalex.org/I1323252656","display_name":"Information Technology University","ror":"https://ror.org/00ngv8j44","country_code":"PK","type":"education","lineage":["https://openalex.org/I1323252656"]},{"id":"https://openalex.org/I992397","display_name":"University of Bor\u00e5s","ror":"https://ror.org/01fdxwh83","country_code":"SE","type":"education","lineage":["https://openalex.org/I992397"]}],"countries":["PK","SE"],"is_corresponding":false,"raw_author_name":"Henrik Linusson","raw_affiliation_strings":["Department of Information Technology, University of Bor\u00e5s, Sweden","[Dept. of Information Technology, University of Bor\u00e5s, Sweden]"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, University of Bor\u00e5s, Sweden","institution_ids":["https://openalex.org/I992397"]},{"raw_affiliation_string":"[Dept. of Information Technology, University of Bor\u00e5s, Sweden]","institution_ids":["https://openalex.org/I1323252656"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103036745"],"corresponding_institution_ids":["https://openalex.org/I1323252656","https://openalex.org/I992397"],"apc_list":null,"apc_paid":null,"fwci":0.4314,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75122086,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998000264167786,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998000264167786,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9998000264167786,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9980000257492065,"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/nonconformity","display_name":"Nonconformity","score":0.8906152844429016},{"id":"https://openalex.org/keywords/conformal-map","display_name":"Conformal map","score":0.6509638428688049},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5622762441635132},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5445488095283508},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5433623790740967},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4876788854598999},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.45466485619544983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43993180990219116},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.43796974420547485},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43776458501815796},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4198739528656006},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3866621255874634},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.34332627058029175},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3389330506324768},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.10928097367286682}],"concepts":[{"id":"https://openalex.org/C2781103444","wikidata":"https://www.wikidata.org/wiki/Q7049238","display_name":"Nonconformity","level":2,"score":0.8906152844429016},{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.6509638428688049},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5622762441635132},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5445488095283508},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5433623790740967},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4876788854598999},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.45466485619544983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43993180990219116},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.43796974420547485},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43776458501815796},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4198739528656006},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3866621255874634},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.34332627058029175},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3389330506324768},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.10928097367286682},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2015.7280763","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280763","pdf_url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7280763","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/ijcnn.2015.7280763","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280763","pdf_url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7280763","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1621275771.pdf","grobid_xml":"https://content.openalex.org/works/W1621275771.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W11231031","https://openalex.org/W93812805","https://openalex.org/W1499689786","https://openalex.org/W1521746852","https://openalex.org/W1553101044","https://openalex.org/W1565315670","https://openalex.org/W1565746575","https://openalex.org/W1589298886","https://openalex.org/W1594344279","https://openalex.org/W1974758710","https://openalex.org/W1984590107","https://openalex.org/W2010546252","https://openalex.org/W2027166444","https://openalex.org/W2039636933","https://openalex.org/W2070847992","https://openalex.org/W2120045164","https://openalex.org/W2130211925","https://openalex.org/W2143059037","https://openalex.org/W2154689719","https://openalex.org/W2163517193","https://openalex.org/W2182722412","https://openalex.org/W2306391144","https://openalex.org/W3120740533","https://openalex.org/W4212883601","https://openalex.org/W4238893454","https://openalex.org/W6603889159","https://openalex.org/W6698059703"],"related_works":["https://openalex.org/W1608624584","https://openalex.org/W4200414339","https://openalex.org/W2327615228","https://openalex.org/W4245197589","https://openalex.org/W2998399529","https://openalex.org/W1995578729","https://openalex.org/W2013327011","https://openalex.org/W3039848032","https://openalex.org/W2336700393","https://openalex.org/W2077488434"],"abstract_inverted_index":{"Conformal":[0],"predictors":[1,22,46,59,225],"use":[2],"machine":[3],"learning":[4],"models":[5],"to":[6,82,132,221,235],"output":[7],"prediction":[8,13,18,55,85,162],"sets.":[9,56],"For":[10],"regression,":[11],"a":[12,17,36,67,71,99,141],"set":[14,72,143],"is":[15,33,47,144,167,231],"simply":[16],"interval.":[19],"All":[20],"conformal":[21,45,58,89,110,224],"are":[23,94,112,126,203],"valid,":[24],"meaning":[25],"that":[26,155],"the":[27,51,54,79,84,91,102,130,165,171,174,181,188,195,236],"error":[28,197],"rate":[29],"on":[30,114,134,170,215,226],"novel":[31],"data":[32,152,228],"bounded":[34],"by":[35,193],"preset":[37],"significance":[38],"level.":[39],"The":[40,146],"key":[41],"performance":[42],"metric":[43],"for":[44,78],"their":[48],"efficiency,":[49],"i.e.,":[50,70,96],"size":[52],"of":[53,73,104,116,118,138,173,190,198],"Inductive":[57],"utilize":[60],"real-valued":[61],"functions,":[62,65],"called":[63],"nonconformity":[64,92,124,157,185],"and":[66,122],"calibration":[68,142,243],"set,":[69],"labeled":[74],"instances":[75,136],"not":[76],"used":[77],"model":[80],"training,":[81],"obtain":[83],"regions.":[86],"In":[87,107,128],"state-of-the-art":[88],"regressors,":[90],"functions":[93,125,158],"normalized,":[95],"they":[97],"include":[98],"component":[100],"estimating":[101],"difficulty":[103,175,189],"each":[105],"instance.":[106],"this":[108,179],"study,":[109,180,239],"regressors":[111],"built":[113],"top":[115],"ensembles":[117],"bagged":[119],"neural":[120],"networks,":[121],"several":[123],"evaluated.":[127],"addition,":[129],"option":[131],"calibrate":[133],"out-of-bag":[135,216],"instead":[137],"setting":[139],"aside":[140],"investigated.":[145],"experiments,":[147],"using":[148,208],"33":[149],"publicly":[150],"available":[151],"sets,":[153,163,229],"show":[154],"normalized":[156,184],"can":[159],"produce":[160],"smaller":[161,227],"but":[164],"efficiency":[166],"highly":[168],"dependent":[169],"quality":[172],"estimation.":[176],"Specifically,":[177],"in":[178,232],"most":[182],"efficient":[183,223],"function":[186],"estimated":[187],"an":[191],"instance":[192],"calculating":[194],"average":[196],"neighboring":[199],"instances.":[200],"These":[201],"results":[202],"consistent":[204],"with":[205],"previous":[206],"studies":[207],"random":[209,237],"forests":[210],"as":[211],"underlying":[212],"models.":[213],"Calibrating":[214],"did,":[217],"however,":[218],"only":[219],"lead":[220],"more":[222],"which":[230],"sharp":[233],"contrast":[234],"forest":[238],"where":[240],"out-out-of":[241],"bag":[242],"was":[244],"significantly":[245],"better":[246],"overall.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}