{"id":"https://openalex.org/W4403570182","doi":"https://doi.org/10.48550/arxiv.2410.09894","title":"Inductive Conformal Prediction under Data Scarcity: Exploring the Impacts of Nonconformity Measures","display_name":"Inductive Conformal Prediction under Data Scarcity: Exploring the Impacts of Nonconformity Measures","publication_year":2024,"publication_date":"2024-10-13","ids":{"openalex":"https://openalex.org/W4403570182","doi":"https://doi.org/10.48550/arxiv.2410.09894"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2410.09894","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.09894","pdf_url":"https://arxiv.org/pdf/2410.09894","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2410.09894","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114334926","display_name":"Yuko Kato","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kato, Yuko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114334927","display_name":"David M. J. Tax","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tax, David M. J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5114334928","display_name":"Marco Loog","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Loog, Marco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9635000228881836,"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/T10320","display_name":"Neural Networks and Applications","score":0.9635000228881836,"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":0.9524781703948975},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.6251259446144104},{"id":"https://openalex.org/keywords/conformal-map","display_name":"Conformal map","score":0.5884053111076355},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.34018564224243164},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2138848900794983},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.19807037711143494},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.08760946989059448},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.04986763000488281}],"concepts":[{"id":"https://openalex.org/C2781103444","wikidata":"https://www.wikidata.org/wiki/Q7049238","display_name":"Nonconformity","level":2,"score":0.9524781703948975},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.6251259446144104},{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.5884053111076355},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.34018564224243164},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2138848900794983},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.19807037711143494},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.08760946989059448},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.04986763000488281},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2410.09894","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.09894","pdf_url":"https://arxiv.org/pdf/2410.09894","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2410.09894","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2410.09894","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2410.09894","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.09894","pdf_url":"https://arxiv.org/pdf/2410.09894","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"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],"prediction,":[1],"which":[2,117],"makes":[3],"no":[4,162],"distributional":[5],"assumptions":[6],"about":[7],"the":[8,38,42,53,85,148,168,171,181,185,200,207,212],"data,":[9,131],"has":[10],"emerged":[11],"as":[12,139,170],"a":[13,33,45,120],"powerful":[14],"and":[15,41,96,103,129,143],"reliable":[16],"approach":[17],"to":[18,83,209],"uncertainty":[19],"quantification":[20],"in":[21,28,99,107,123],"practical":[22],"applications.":[23,126,217],"The":[24,57,76,111],"nonconformity":[25,89,164,175,213],"measure":[26,55,165,176,214],"used":[27,106],"conformal":[29,46,109,151],"prediction":[30,47,152],"quantifies":[31],"how":[32,134],"test":[34],"sample":[35],"differs":[36],"from":[37],"training":[39],"data":[40],"effectiveness":[43,172],"of":[44,59,74,79,87,101,150,173,184,202],"interval":[48],"may":[49],"depend":[50],"heavily":[51,178],"on":[52,114],"precise":[54],"employed.":[56],"impact":[58],"this":[60,80],"choice":[61],"has,":[62],"however,":[63],"not":[64,195],"been":[65],"widely":[66],"explored,":[67],"especially":[68],"when":[69,105],"dealing":[70],"with":[71],"limited":[72],"amounts":[73],"data.":[75,186],"primary":[77],"objective":[78],"study":[81],"is":[82,113,118,177],"evaluate":[84],"performance":[86],"various":[88],"measures":[90],"(absolute":[91],"error-based,":[92,95],"normalized":[93],"absolute":[94],"quantile-based":[97],"measures)":[98],"terms":[100],"validity":[102],"efficiency":[104,149],"inductive":[108],"prediction.":[110],"focus":[112],"small":[115],"datasets,":[116],"still":[119],"common":[121],"setting":[122],"many":[124],"real-world":[125,130],"Using":[127],"synthetic":[128],"we":[132,188],"assess":[133],"different":[135,216],"characteristics":[136],"--":[137,145],"such":[138],"dataset":[140,192],"size,":[141],"noise,":[142],"dimensionality":[144],"can":[146],"affect":[147],"intervals.":[153],"Our":[154],"results":[155],"show":[156],"that":[157,190],"although":[158],"there":[159],"are":[160],"differences,":[161],"single":[163],"consistently":[166],"outperforms":[167],"others,":[169],"each":[174],"influenced":[179],"by":[180],"specific":[182],"nature":[183],"Additionally,":[187],"found":[189],"increasing":[191],"size":[193],"does":[194],"always":[196],"improve":[197],"efficiency,":[198],"suggesting":[199],"importance":[201],"fine-tuning":[203],"models":[204],"and,":[205],"again,":[206],"need":[208],"carefully":[210],"select":[211],"for":[215]},"counts_by_year":[],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
