{"id":"https://openalex.org/W2021332099","doi":"https://doi.org/10.1142/s021800140300240x","title":"KERNEL WHITENING FOR ONE-CLASS CLASSIFICATION","display_name":"KERNEL WHITENING FOR ONE-CLASS CLASSIFICATION","publication_year":2003,"publication_date":"2003-05-01","ids":{"openalex":"https://openalex.org/W2021332099","doi":"https://doi.org/10.1142/s021800140300240x","mag":"2021332099"},"language":"en","primary_location":{"id":"doi:10.1142/s021800140300240x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021800140300240x","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5001295629","display_name":"David M. J. Tax","orcid":"https://orcid.org/0000-0002-5153-9087"},"institutions":[{"id":"https://openalex.org/I4923324","display_name":"Fraunhofer-Gesellschaft","ror":"https://ror.org/05hkkdn48","country_code":"DE","type":"government","lineage":["https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"DAVID M. J. TAX","raw_affiliation_strings":["Fraunhofer Institute FIRST.IDA, Kekul\u00e9str.7, D-12489 Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute FIRST.IDA, Kekul\u00e9str.7, D-12489 Berlin, Germany","institution_ids":["https://openalex.org/I4923324"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065579866","display_name":"Piotr Juszczak","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"PIOTR JUSZCZAK","raw_affiliation_strings":["Pattern Recognition Group, Faculty of Applied Science, Delft University of Technology, Lorentzweg 1, 2628\u00a0CJ Delft, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition Group, Faculty of Applied Science, Delft University of Technology, Lorentzweg 1, 2628\u00a0CJ Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3223,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.89463568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"17","issue":"03","first_page":"333","last_page":"347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9933000206947327,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9926000237464905,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6961637139320374},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6708353161811829},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6494683027267456},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6199946999549866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6017834544181824},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.5816672444343567},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5405205488204956},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5302151441574097},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.4884251654148102},{"id":"https://openalex.org/keywords/hypersphere","display_name":"Hypersphere","score":0.48160192370414734},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4541934132575989},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4242575466632843},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3119547367095947}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6961637139320374},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6708353161811829},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6494683027267456},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6199946999549866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6017834544181824},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.5816672444343567},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5405205488204956},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5302151441574097},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.4884251654148102},{"id":"https://openalex.org/C2776562905","wikidata":"https://www.wikidata.org/wiki/Q306610","display_name":"Hypersphere","level":2,"score":0.48160192370414734},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4541934132575989},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4242575466632843},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3119547367095947},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1142/s021800140300240x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021800140300240x","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.10.8659","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.8659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ida.first.fhg.de/publications/JusTaxDui02.ps","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.19.3274","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.19.3274","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ph.tn.tudelft.nl/People/bob/papers/svm_02_occ.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.73.3509","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.73.3509","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ida.first.fhg.de/publications/JusTaxDui02.pdf","raw_type":"text"},{"id":"pmh:oai:fraunhofer.de:N-38341","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-38341.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer FIRST","raw_type":"Journal Article"},{"id":"pmh:oai:publica.fraunhofer.de:publica/205210","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/205210","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"journal article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310567","display_name":"Boston Scientific Corporation","ror":"https://ror.org/0385es521"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320323564","display_name":"Politechnika Wroc\u0142awska","ror":"https://ror.org/008fyn775"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2074399002","https://openalex.org/W2105298717","https://openalex.org/W2140095548","https://openalex.org/W2492794003","https://openalex.org/W4240338048","https://openalex.org/W4254721730","https://openalex.org/W4388297464"],"related_works":["https://openalex.org/W2142265066","https://openalex.org/W2014235090","https://openalex.org/W2787396923","https://openalex.org/W4301075504","https://openalex.org/W2886321183","https://openalex.org/W2963848714","https://openalex.org/W2056283567","https://openalex.org/W1565299197","https://openalex.org/W2088032561","https://openalex.org/W2542234468"],"abstract_inverted_index":{"In":[0,47],"one-class":[1,72],"classification":[2],"one":[3],"tries":[4,101],"to":[5,13,36,49,102,106,115,126,135],"describe":[6],"a":[7,51,95,107,131,156],"class":[8],"of":[9,63,70,79],"target":[10,56],"data":[11,65,81,87,105,116,129,140],"and":[12,58,82,111,166],"distinguish":[14],"it":[15],"from":[16,123],"all":[17],"other":[18],"possible":[19],"outlier":[20],"objects.":[21],"Obvious":[22],"applications":[23],"are":[24,28],"areas":[25],"where":[26],"outliers":[27],"very":[29,32,145],"diverse":[30],"or":[31,34,43],"difficult":[33],"expensive":[35],"measure,":[37],"such":[38],"as":[39],"in":[40,44,89,118,130],"machine":[41],"diagnostics":[42],"medical":[45],"applications.":[46],"order":[48],"have":[50],"good":[52,61],"distinction":[53],"between":[54],"the":[55,59,64,77,80,104,128,148,159,164],"objects":[57],"outliers,":[60],"representation":[62],"is":[66,83,112],"essential.":[67],"The":[68,161],"performance":[69],"many":[71],"classifiers":[73],"critically":[74],"depends":[75],"on":[76],"scaling":[78],"often":[84],"harmed":[85],"by":[86,147],"distributions":[88],"(nonlinear)":[90],"subspaces.":[91,119],"This":[92,138],"paper":[93,162],"presents":[94,163],"simple":[96],"preprocessing":[97],"method":[98],"which":[99,153],"actively":[100],"map":[103],"spherical":[108],"symmetric":[109],"cluster":[110],"almost":[113],"insensitive":[114],"distributed":[117],"It":[120],"uses":[121],"techniques":[122],"Kernel":[124],"PCA":[125],"rescale":[127],"kernel":[132],"feature":[133],"space":[134],"unit":[136],"variance.":[137],"transformed":[139],"can":[141],"now":[142],"be":[143],"described":[144],"well":[146],"Support":[149],"Vector":[150],"Data":[151],"Description,":[152],"basically":[154],"fits":[155],"hypersphere":[157],"around":[158],"data.":[160],"methods":[165],"some":[167],"preliminary":[168],"experimental":[169],"results.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}