{"id":"https://openalex.org/W3107875665","doi":"https://doi.org/10.1109/iccp51029.2020.9266240","title":"Conformal transformation of the metric for k-nearest neighbors classification","display_name":"Conformal transformation of the metric for k-nearest neighbors classification","publication_year":2020,"publication_date":"2020-09-03","ids":{"openalex":"https://openalex.org/W3107875665","doi":"https://doi.org/10.1109/iccp51029.2020.9266240","mag":"3107875665"},"language":"en","primary_location":{"id":"doi:10.1109/iccp51029.2020.9266240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp51029.2020.9266240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5005141679","display_name":"Marius Claudiu Popescu","orcid":null},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Marius Claudiu Popescu","raw_affiliation_strings":["Signal Processing Group, Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal Processing Group, Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072184884","display_name":"L\u0103crimioara Grama","orcid":"https://orcid.org/0000-0003-0383-5196"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Lacrimioara Grama","raw_affiliation_strings":["Signal Processing Group, Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal Processing Group, Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036243309","display_name":"Corneliu Rusu","orcid":"https://orcid.org/0000-0001-5209-2734"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Corneliu Rusu","raw_affiliation_strings":["Signal Processing Group, Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal Processing Group, Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158333966"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.1491723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"37","issue":null,"first_page":"229","last_page":"234"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9977999925613403,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973999857902527,"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":0.996399998664856,"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/conformal-map","display_name":"Conformal map","score":0.7346305251121521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6244328618049622},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5712229013442993},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.5675778388977051},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5494746565818787},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.515494167804718},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.49315088987350464},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4685058891773224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4163481593132019},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39634764194488525},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38180825114250183},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3533626198768616},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32979297637939453},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.09504568576812744}],"concepts":[{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.7346305251121521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6244328618049622},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5712229013442993},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.5675778388977051},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5494746565818787},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.515494167804718},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.49315088987350464},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4685058891773224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4163481593132019},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39634764194488525},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38180825114250183},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3533626198768616},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32979297637939453},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.09504568576812744},{"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccp51029.2020.9266240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp51029.2020.9266240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP)","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":35,"referenced_works":["https://openalex.org/W1944672","https://openalex.org/W182831726","https://openalex.org/W607505555","https://openalex.org/W1495244287","https://openalex.org/W1500117362","https://openalex.org/W1502069036","https://openalex.org/W1510073064","https://openalex.org/W1607807570","https://openalex.org/W1872721118","https://openalex.org/W1898424075","https://openalex.org/W1956559956","https://openalex.org/W1965524806","https://openalex.org/W2026892575","https://openalex.org/W2041406732","https://openalex.org/W2109283550","https://openalex.org/W2113459411","https://openalex.org/W2122111042","https://openalex.org/W2141375237","https://openalex.org/W2498610323","https://openalex.org/W2540093921","https://openalex.org/W2799061466","https://openalex.org/W2921044699","https://openalex.org/W2963057791","https://openalex.org/W2995528299","https://openalex.org/W3013401049","https://openalex.org/W3101477643","https://openalex.org/W3133201098","https://openalex.org/W4205687621","https://openalex.org/W4236362309","https://openalex.org/W4256561644","https://openalex.org/W6639179963","https://openalex.org/W6642162515","https://openalex.org/W6676984168","https://openalex.org/W6680513528","https://openalex.org/W6759870044"],"related_works":["https://openalex.org/W4234886518","https://openalex.org/W2389591058","https://openalex.org/W2364252372","https://openalex.org/W4234066492","https://openalex.org/W2382112581","https://openalex.org/W3124036233","https://openalex.org/W1998063895","https://openalex.org/W4229787472","https://openalex.org/W1967044713","https://openalex.org/W2486541857"],"abstract_inverted_index":{"The":[0,88],"paper":[1],"introduces":[2],"a":[3,25,43,68,74,79,95,123,136,148],"new":[4],"method":[5,76,104,121],"for":[6,77],"improving":[7],"the":[8,17,21,60,63,109,114,120,130,139,144],"nearest":[9],"neighbors":[10],"classifier.":[11],"Our":[12],"approach":[13],"is":[14,32,38,81],"based":[15],"on":[16,85],"idea":[18],"of":[19,45,91,138,143,150],"replacing":[20],"constant":[22],"metric":[23],"with":[24,94,135],"variable":[26],"and":[27,35,99,141,146],"conformally":[28],"equivalent":[29],"one":[30],"that":[31,55,62],"data":[33],"dependent,":[34],"therefore":[36],"it":[37],"more":[39],"informative.":[40],"We":[41],"define":[42],"family":[44],"conformal":[46],"transformations":[47],"that,":[48],"under":[49],"some":[50,106],"assumptions,":[51],"induces":[52],"distance":[53],"functions":[54],"are":[56,93,132],"efficiently":[57],"computable.":[58],"Using":[59],"intuition":[61],"distances":[64],"between":[65],"points":[66],"near":[67],"class":[69],"boundary":[70],"should":[71],"be":[72],"larger,":[73],"simple":[75],"selecting":[78],"transformation":[80],"proposed.We":[82],"perform":[83],"experiments":[84,92],"two":[86],"datasets.":[87],"first":[89],"set":[90],"sentiment":[96],"prediction":[97],"dataset,":[98],"in":[100],"this":[101,128],"case":[102,129],"our":[103],"offers":[105],"improvements":[107],"over":[108],"standard":[110],"k-NN":[111],"algorithm.":[112],"In":[113,127],"second":[115],"empirical":[116],"analysis,":[117],"we":[118],"apply":[119],"to":[122],"news":[124],"categorisation":[125],"problem.":[126],"results":[131],"mixed.We":[133],"conclude":[134],"discussion":[137],"advantages":[140],"weaknesses":[142],"method,":[145],"propose":[147],"number":[149],"possible":[151],"improvements.":[152]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
