{"id":"https://openalex.org/W2055084746","doi":"https://doi.org/10.1109/icmlc.2010.5581059","title":"Multiple nearest neighbor classifiers system based on feature perturbation by mutual information","display_name":"Multiple nearest neighbor classifiers system based on feature perturbation by mutual information","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2055084746","doi":"https://doi.org/10.1109/icmlc.2010.5581059","mag":"2055084746"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2010.5581059","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2010.5581059","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on Machine Learning and Cybernetics","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/A5088734112","display_name":"Wang-Li Juan","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wang-Li Juan","raw_affiliation_strings":["Faculty of computer, Guangdong University of Technology, Guangzhou, China","Faculty of Computer, Guangdong University of Technology, Guangzhou 510006)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of computer, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"Faculty of Computer, Guangdong University of Technology, Guangzhou 510006)","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5088734112"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1679416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":null,"first_page":"247","last_page":"251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9993000030517578,"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":0.9993000030517578,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9891999959945679,"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":0.9872000217437744,"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/random-subspace-method","display_name":"Random subspace method","score":0.7329093217849731},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.7271100282669067},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7157543301582336},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6824139952659607},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.6811812520027161},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6328996419906616},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6083234548568726},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5248627662658691},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.45782244205474854},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4193102717399597},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33884286880493164}],"concepts":[{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.7329093217849731},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.7271100282669067},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7157543301582336},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6824139952659607},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.6811812520027161},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6328996419906616},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6083234548568726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5248627662658691},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.45782244205474854},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4193102717399597},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33884286880493164}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc.2010.5581059","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2010.5581059","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on Machine Learning and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321949","display_name":"Department of Education of Hebei Province","ror":"https://ror.org/01jkyjd96"},{"id":"https://openalex.org/F4320325030","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W61567823","https://openalex.org/W1578627936","https://openalex.org/W1988790447","https://openalex.org/W2038567802","https://openalex.org/W2109094355","https://openalex.org/W2113242816","https://openalex.org/W2113890143","https://openalex.org/W2124868070","https://openalex.org/W2149772057","https://openalex.org/W2155720957","https://openalex.org/W2156483112","https://openalex.org/W2487087946","https://openalex.org/W2912934387","https://openalex.org/W4212883601","https://openalex.org/W4248437541","https://openalex.org/W6602592809","https://openalex.org/W6634715548"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W4391160746","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W2375795576","https://openalex.org/W2985680200"],"abstract_inverted_index":{"In":[0,80,125,203],"this":[1,20,81],"paper,":[2,82],"a":[3],"feature":[4,29,59,152,165,191],"perturbation":[5,30,166,192],"by":[6,86,122,154,167,193],"mutual":[7,87,123,155,194],"information":[8,88,195],"is":[9,89,102,144,178,196,214],"proposed":[10,84,133,142,212],"and":[11,70,110],"multiple":[12,52,158,175,184],"nearest":[13,23,37,53,159,185],"neighbor":[14,24,38,54,160,186],"classifiers":[15,25,55,101,161,176,187,209],"are":[16,48,119,138],"combined":[17],"according":[18],"to":[19,63,73,91,104,127,180],"way.":[21],"Multiple":[22],"system":[26,56,162,177,188],"based":[27,57,163,189],"on":[28,58,164,190],"can":[31],"improve":[32],"the":[33,42,65,83,93,106,112,129,132,141,205,211],"performance":[34],"of":[35,44,67,99,108,131,207],"single":[36,181],"classifier":[39,118],"biased":[40],"with":[41],"curse":[43],"dimensionality.":[45],"However,":[46],"there":[47],"two":[49,94],"problems":[50],"in":[51,210],"perturbation:":[60],"(i)":[61,96,147],"how":[62,72],"determine":[64],"number":[66,98,107,206],"component":[68,78,100,117,208],"classifiers,":[69],"(ii)":[71,111,149],"select":[74],"features":[75,114],"for":[76,115],"each":[77,116],"classifier.":[79,182],"method":[85,143,213],"able":[90],"solve":[92],"problems.":[95],"The":[97,170],"set":[103],"be":[105],"classes,":[109],"selected":[113],"automatically":[120],"determined":[121],"information.":[124],"order":[126],"evaluate":[128],"effectiveness":[130],"method,":[134],"three":[135],"UCI":[136],"datasets":[137],"selected.":[139],"And":[140,183],"compared":[145],"with:":[146],"NNC,":[148],"NNC":[150],"after":[151],"selection":[153],"information,":[156],"(iii)":[157],"attribute":[168],"bagging.":[169],"experimental":[171],"results":[172],"show":[173],"that":[174],"superior":[179],"better":[197],"than":[198,216],"any":[199,217],"other":[200,218],"combination":[201],"methods.":[202,219],"addition,":[204],"less":[215]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}