{"id":"https://openalex.org/W2735610538","doi":"https://doi.org/10.1109/ijcnn.2017.7966105","title":"Model-agnostic nonconformity functions for conformal classification","display_name":"Model-agnostic nonconformity functions for conformal classification","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2735610538","doi":"https://doi.org/10.1109/ijcnn.2017.7966105","mag":"2735610538"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7966105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966105","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5103036745","display_name":"Ulf Johansson","orcid":"https://orcid.org/0000-0003-0412-6199"},"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/I94616838","display_name":"J\u00f6nk\u00f6ping University","ror":"https://ror.org/03t54am93","country_code":"SE","type":"education","lineage":["https://openalex.org/I94616838"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Ulf Johansson","raw_affiliation_strings":["Dept. of Computer Science and Informatics, J\u00f6nk\u00f6ping University, Sweden","Dept. of Information Technology, University of Bor\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Informatics, J\u00f6nk\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I94616838"]},{"raw_affiliation_string":"Dept. of Information Technology, University of Bor\u00e5s, Sweden","institution_ids":["https://openalex.org/I992397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059387263","display_name":"Henrik Linusson","orcid":null},"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"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Henrik Linusson","raw_affiliation_strings":["Dept. of Information Technology, University of Bor\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"Dept. of Information Technology, University of Bor\u00e5s, Sweden","institution_ids":["https://openalex.org/I992397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073489496","display_name":"Tuve L\u00f6fstr\u00f6m","orcid":"https://orcid.org/0000-0003-0274-9026"},"institutions":[{"id":"https://openalex.org/I94616838","display_name":"J\u00f6nk\u00f6ping University","ror":"https://ror.org/03t54am93","country_code":"SE","type":"education","lineage":["https://openalex.org/I94616838"]},{"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":["SE"],"is_corresponding":false,"raw_author_name":"Tuve Lofstrom","raw_affiliation_strings":["Dept. of Computer Science and Informatics, J\u00f6nk\u00f6ping University, Sweden","Dept. of Information Technology, University of Bor\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Informatics, J\u00f6nk\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I94616838"]},{"raw_affiliation_string":"Dept. of Information Technology, University of Bor\u00e5s, Sweden","institution_ids":["https://openalex.org/I992397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033008105","display_name":"Henrik Bostr\u00f6m","orcid":"https://orcid.org/0000-0001-8382-0300"},"institutions":[{"id":"https://openalex.org/I161593684","display_name":"Stockholm University","ror":"https://ror.org/05f0yaq80","country_code":"SE","type":"education","lineage":["https://openalex.org/I161593684"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Henrik Bostrom","raw_affiliation_strings":["Dept. of Computer and Systems Sciences, Stockholm University, Sweden"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer and Systems Sciences, Stockholm University, Sweden","institution_ids":["https://openalex.org/I161593684"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103036745"],"corresponding_institution_ids":["https://openalex.org/I94616838","https://openalex.org/I992397"],"apc_list":null,"apc_paid":null,"fwci":0.7801,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.79084707,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2072","last_page":"2079"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994999766349792,"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":0.9994999766349792,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9986000061035156,"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":0.9977999925613403,"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":0.9806416034698486},{"id":"https://openalex.org/keywords/conformal-map","display_name":"Conformal map","score":0.722507119178772},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6279988884925842},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5793178677558899},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5001883506774902},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4775320291519165},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4539574682712555},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4392509460449219},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35356006026268005},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3346521258354187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2911475598812103},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.15955060720443726},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09132122993469238}],"concepts":[{"id":"https://openalex.org/C2781103444","wikidata":"https://www.wikidata.org/wiki/Q7049238","display_name":"Nonconformity","level":2,"score":0.9806416034698486},{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.722507119178772},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6279988884925842},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5793178677558899},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5001883506774902},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4775320291519165},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4539574682712555},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4392509460449219},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35356006026268005},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3346521258354187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2911475598812103},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.15955060720443726},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09132122993469238},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2017.7966105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966105","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W11231031","https://openalex.org/W108703714","https://openalex.org/W1499689786","https://openalex.org/W1521746852","https://openalex.org/W1553101044","https://openalex.org/W1565315670","https://openalex.org/W1652955026","https://openalex.org/W1786598644","https://openalex.org/W1974758710","https://openalex.org/W1984590107","https://openalex.org/W2027166444","https://openalex.org/W2034323583","https://openalex.org/W2070847992","https://openalex.org/W2073241381","https://openalex.org/W2102608190","https://openalex.org/W2120045164","https://openalex.org/W2130211925","https://openalex.org/W2143059037","https://openalex.org/W2154689719","https://openalex.org/W2155250714","https://openalex.org/W2163517193","https://openalex.org/W2169284845","https://openalex.org/W2298227532","https://openalex.org/W2466730232","https://openalex.org/W2469403471","https://openalex.org/W2523257400","https://openalex.org/W3120740533","https://openalex.org/W4212883601","https://openalex.org/W4238893454","https://openalex.org/W6675489184","https://openalex.org/W6684862044","https://openalex.org/W6727355587"],"related_works":["https://openalex.org/W1608624584","https://openalex.org/W4200414339","https://openalex.org/W4245197589","https://openalex.org/W2327615228","https://openalex.org/W2998399529","https://openalex.org/W2013327011","https://openalex.org/W3039848032","https://openalex.org/W2888894362","https://openalex.org/W2077488434","https://openalex.org/W2015716952"],"abstract_inverted_index":{"A":[0],"conformal":[1,15,43,66,138],"predictor":[2],"outputs":[3],"prediction":[4,51,57],"regions,":[5,52],"for":[6,41,137],"classification":[7],"label":[8,198],"sets.":[9],"The":[10,140],"key":[11,38],"property":[12],"of":[13,48,75,87,129,146,175],"all":[14],"predictors":[16,44],"is":[17,29,45,182],"that":[18,143,158],"they":[19,110],"are":[20,59,104,132],"valid,":[21],"i.e.,":[22],"their":[23],"error":[24],"rate":[25],"on":[26,69,84,100,116,153,166,191,200],"novel":[27],"data":[28,121],"bounded":[30],"by":[31],"a":[32,150,172,178,187],"preset":[33],"significance":[34],"level.":[35],"Thus,":[36],"the":[37,46,49,73,80,85,88,114,144,154,167,183,192,196],"performance":[39],"metric":[40],"evaluating":[42],"size":[47],"output":[50],"where":[53],"smaller":[54],"(more":[55],"informative)":[56],"regions":[58],"said":[60],"to":[61,108],"be":[62,163],"more":[63],"efficient.":[64],"All":[65],"predictions":[67],"rely":[68],"nonconformity":[70,90,97,147,160,180,188],"functions,":[71,98,103],"measuring":[72],"strangeness":[74],"an":[76],"input-output":[77],"pair,":[78],"and":[79,127],"efficiency":[81,169],"depends":[82],"critically":[83],"quality":[86],"chosen":[89],"function.":[91],"In":[92,113],"this":[93],"paper,":[94],"three":[95],"model-agnostic":[96],"based":[99,190],"well-known":[101],"loss":[102,194],"evaluated":[105],"with":[106],"regard":[107],"how":[109],"affect":[111],"efficiency.":[112],"experimentation":[115],"21":[117],"publicly":[118],"available":[119],"multi-class":[120],"sets,":[122],"both":[123],"single":[124],"neural":[125,130],"networks":[126,131],"ensembles":[128],"used":[133,164],"as":[134],"underlying":[135],"models":[136],"classifiers.":[139],"results":[141],"show":[142],"choice":[145],"function":[148,181,189],"has":[149],"major":[151],"impact":[152],"efficiency,":[155],"but":[156],"also":[157],"different":[159],"functions":[161],"should":[162],"depending":[165],"exact":[168],"metric.":[170],"For":[171],"high":[173],"fraction":[174],"single-label":[176],"predictions,":[177],"margin-based":[179],"best":[184],"option,":[185],"while":[186],"hinge":[193],"obtained":[195],"smallest":[197],"sets":[199],"average.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
