{"id":"https://openalex.org/W4398349452","doi":"https://doi.org/10.3390/make6020052","title":"Locally-Scaled Kernels and Confidence Voting","display_name":"Locally-Scaled Kernels and Confidence Voting","publication_year":2024,"publication_date":"2024-05-23","ids":{"openalex":"https://openalex.org/W4398349452","doi":"https://doi.org/10.3390/make6020052"},"language":"en","primary_location":{"id":"doi:10.3390/make6020052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6020052","pdf_url":"https://www.mdpi.com/2504-4990/6/2/52/pdf?version=1716456602","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/6/2/52/pdf?version=1716456602","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089386852","display_name":"Elizabeth Hofer","orcid":"https://orcid.org/0009-0004-3689-5923"},"institutions":[{"id":"https://openalex.org/I98251732","display_name":"McMaster University","ror":"https://ror.org/02fa3aq29","country_code":"CA","type":"education","lineage":["https://openalex.org/I98251732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Elizabeth Hofer","raw_affiliation_strings":["Department of Computing and Software, McMaster University, Hamilton, ON L8S 4L8, Canada"],"raw_orcid":"https://orcid.org/0009-0004-3689-5923","affiliations":[{"raw_affiliation_string":"Department of Computing and Software, McMaster University, Hamilton, ON L8S 4L8, Canada","institution_ids":["https://openalex.org/I98251732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082120994","display_name":"Martin v. Mohrenschildt","orcid":"https://orcid.org/0000-0003-1390-620X"},"institutions":[{"id":"https://openalex.org/I98251732","display_name":"McMaster University","ror":"https://ror.org/02fa3aq29","country_code":"CA","type":"education","lineage":["https://openalex.org/I98251732"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Martin v. Mohrenschildt","raw_affiliation_strings":["Department of Computing and Software, McMaster University, Hamilton, ON L8S 4L8, Canada"],"raw_orcid":"https://orcid.org/0000-0003-1390-620X","affiliations":[{"raw_affiliation_string":"Department of Computing and Software, McMaster University, Hamilton, ON L8S 4L8, Canada","institution_ids":["https://openalex.org/I98251732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5082120994"],"corresponding_institution_ids":["https://openalex.org/I98251732"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.6952,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68966274,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"6","issue":"2","first_page":"1126","last_page":"1144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9962000250816345,"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":0.9962000250816345,"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/T10320","display_name":"Neural Networks and Applications","score":0.9930999875068665,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9821000099182129,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.677129864692688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38936060667037964},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.266549289226532},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.07999354600906372},{"id":"https://openalex.org/keywords/politics","display_name":"Politics","score":0.06066611409187317}],"concepts":[{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.677129864692688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38936060667037964},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.266549289226532},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.07999354600906372},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.06066611409187317}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make6020052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6020052","pdf_url":"https://www.mdpi.com/2504-4990/6/2/52/pdf?version=1716456602","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e6a69eab0af14a01870d912ea0e21858","is_oa":false,"landing_page_url":"https://doaj.org/article/e6a69eab0af14a01870d912ea0e21858","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 6, Iss 2, Pp 1126-1144 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make6020052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6020052","pdf_url":"https://www.mdpi.com/2504-4990/6/2/52/pdf?version=1716456602","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G3095605597","display_name":null,"funder_award_id":"IT17587","funder_id":"https://openalex.org/F4320322675","funder_display_name":"Mitacs"}],"funders":[{"id":"https://openalex.org/F4320322675","display_name":"Mitacs","ror":"https://ror.org/00cjrc276"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4398349452.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1495400410","https://openalex.org/W1965524806","https://openalex.org/W2001141328","https://openalex.org/W2032477387","https://openalex.org/W2048430744","https://openalex.org/W2049292654","https://openalex.org/W2055177080","https://openalex.org/W2097308346","https://openalex.org/W2122111042","https://openalex.org/W2124135342","https://openalex.org/W2154468723","https://openalex.org/W2170505850","https://openalex.org/W2187089797","https://openalex.org/W2203714058","https://openalex.org/W2216928620","https://openalex.org/W2598849564","https://openalex.org/W2622869899","https://openalex.org/W2888728157","https://openalex.org/W2889326414","https://openalex.org/W2896248782","https://openalex.org/W2945020349","https://openalex.org/W2950787058","https://openalex.org/W2963693826","https://openalex.org/W2973651390","https://openalex.org/W2989345584","https://openalex.org/W3098996042","https://openalex.org/W3101477643","https://openalex.org/W3105578466","https://openalex.org/W3123421154","https://openalex.org/W4205952436","https://openalex.org/W4206658128","https://openalex.org/W4221109804","https://openalex.org/W4385457675","https://openalex.org/W4385576721","https://openalex.org/W6662507819","https://openalex.org/W6688255819","https://openalex.org/W6806622010"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Classification,":[0],"the":[1,5,41,46,69,84,89,121,140,144,149,161,171,194,200],"task":[2],"of":[3,7,17,25,31,34,43,48,86,91,102,115,143,151,170,202],"discerning":[4],"class":[6],"an":[8,77],"unlabeled":[9],"data":[10,19],"point":[11],"using":[12],"information":[13],"from":[14],"a":[15,22,29,100,113,134,167],"set":[16],"labeled":[18],"points,":[20],"is":[21,80],"well-studied":[23],"area":[24],"machine":[26],"learning":[27],"with":[28,155,175,187],"variety":[30,114],"approaches.":[32],"Many":[33],"these":[35],"approaches":[36],"are":[37],"closely":[38],"linked":[39],"to":[40,62,67,82,123,166,193],"selection":[42],"metrics":[44,54],"or":[45,55,88],"generalizing":[47],"similarities":[49],"defined":[50],"by":[51,127],"kernels.":[52],"These":[53],"similarity":[56,136],"measures":[57],"often":[58],"require":[59,120],"their":[60],"parameters":[61,122,158,178],"be":[63,124],"tuned":[64],"in":[65,94,108],"order":[66],"achieve":[68],"highest":[70,162],"accuracy":[71,150,163,192],"for":[72],"each":[73],"dataset.":[74],"For":[75],"example,":[76],"extensive":[78],"search":[79],"required":[81],"determine":[83],"value":[85],"K":[87],"choice":[90],"distance":[92],"metric":[93],"K-NN":[95,152,196],"classification.":[96],"This":[97,146],"paper":[98],"explores":[99],"method":[101],"kernel":[103,173,185],"construction":[104],"that":[105,138,159],"when":[106],"used":[107,186],"classification":[109],"performs":[110],"consistently":[111],"over":[112],"datasets":[116],"and":[117],"does":[118],"not":[119],"tuned.":[125],"Inspired":[126],"dimensionality":[128],"reduction":[129],"techniques":[130],"(DRT),":[131],"we":[132],"construct":[133],"kernel-based":[135],"measure":[137],"captures":[139],"topological":[141],"structure":[142],"data.":[145],"work":[147],"compares":[148],"classifiers,":[153],"computed":[154],"specific":[156],"operating":[157,203],"obtain":[160],"per":[164],"dataset,":[165],"single":[168],"trial":[169],"here-proposed":[172,184],"classifier":[174],"no":[176],"specialized":[177],"on":[179],"standard":[180],"benchmark":[181],"sets.":[182],"The":[183],"simple":[188],"classifiers":[189,197],"has":[190],"comparable":[191],"\u2018best-case\u2019":[195],"without":[198],"requiring":[199],"tuning":[201],"parameters.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
