{"id":"https://openalex.org/W1985224802","doi":"https://doi.org/10.1109/grc.2008.4664742","title":"Study of ensemble method of classifiers for neural networks based on K-means clustering","display_name":"Study of ensemble method of classifiers for neural networks based on K-means clustering","publication_year":2008,"publication_date":"2008-08-01","ids":{"openalex":"https://openalex.org/W1985224802","doi":"https://doi.org/10.1109/grc.2008.4664742","mag":"1985224802"},"language":"en","primary_location":{"id":"doi:10.1109/grc.2008.4664742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2008.4664742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Granular Computing","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/A5100399824","display_name":"Kai Li","orcid":"https://orcid.org/0000-0001-8452-620X"},"institutions":[{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Li","raw_affiliation_strings":["School of mathematics and computer, Hebei University, Baoding, China","Sch. of Math. & Comput., Hebei Univ., Baoding"],"affiliations":[{"raw_affiliation_string":"School of mathematics and computer, Hebei University, Baoding, China","institution_ids":["https://openalex.org/I43337087"]},{"raw_affiliation_string":"Sch. of Math. & Comput., Hebei Univ., Baoding","institution_ids":["https://openalex.org/I43337087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111575190","display_name":"Shengling Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengling Chang","raw_affiliation_strings":["School of mathematics and computer, Hebei University, Baoding, China","Sch. of Math. & Comput., Hebei Univ., Baoding"],"affiliations":[{"raw_affiliation_string":"School of mathematics and computer, Hebei University, Baoding, China","institution_ids":["https://openalex.org/I43337087"]},{"raw_affiliation_string":"Sch. of Math. & Comput., Hebei Univ., Baoding","institution_ids":["https://openalex.org/I43337087"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100399824"],"corresponding_institution_ids":["https://openalex.org/I43337087"],"apc_list":null,"apc_paid":null,"fwci":0.2944558,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62511536,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"375","last_page":"378"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9939000010490417,"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":0.9939000010490417,"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":0.9861999750137329,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9498999714851379,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7540589570999146},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7515573501586914},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.7211475372314453},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.710529625415802},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7051223516464233},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6575590372085571},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.6148931980133057},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5660161972045898},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5337200164794922},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5000677108764648},{"id":"https://openalex.org/keywords/cascading-classifiers","display_name":"Cascading classifiers","score":0.4753163456916809},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"k-means clustering","score":0.42714792490005493},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39855366945266724}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7540589570999146},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7515573501586914},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.7211475372314453},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.710529625415802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7051223516464233},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6575590372085571},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.6148931980133057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5660161972045898},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5337200164794922},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5000677108764648},{"id":"https://openalex.org/C40651066","wikidata":"https://www.wikidata.org/wiki/Q5048220","display_name":"Cascading classifiers","level":4,"score":0.4753163456916809},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.42714792490005493},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39855366945266724}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/grc.2008.4664742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2008.4664742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Granular Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2015437745","https://openalex.org/W2034784249","https://openalex.org/W2058307353","https://openalex.org/W2100128988","https://openalex.org/W2103718437","https://openalex.org/W2164544703","https://openalex.org/W2982720039","https://openalex.org/W6684636516"],"related_works":["https://openalex.org/W2046975922","https://openalex.org/W2057416691","https://openalex.org/W1819627533","https://openalex.org/W2104246955","https://openalex.org/W4256395896","https://openalex.org/W2968660735","https://openalex.org/W2245276335","https://openalex.org/W1760344465","https://openalex.org/W1985828740","https://openalex.org/W2145836532"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"diversity":[2,16],"being":[3],"a":[4,32,73],"necessary":[5],"condition":[6],"of":[7,17,69,82,85,94],"the":[8,18,62,67,83,86,92],"ensemble":[9,21,87,95],"learning,":[10],"we":[11,30,60,90],"study":[12,91],"method":[13,96,101],"for":[14],"improving":[15],"neural":[19,46],"networks":[20],"based":[22],"on":[23,53],"K-means":[24,63],"clustering":[25,66],"technique.":[26],"In":[27],"this":[28],"paper,":[29],"propose":[31],"selecting":[33],"approach":[34],"that":[35],"is":[36],"first":[37],"to":[38,50,65,79],"train":[39],"many":[40],"classifiers":[41,70],"through":[42],"training":[43],"set":[44,55],"with":[45,105],"network":[47],"algorithm,":[48],"and":[49,71,102,107],"classify":[51],"data":[52],"validation":[54],"using":[56,98],"classifiers.":[57],"And":[58],"then":[59],"use":[61],"algorithm":[64],"results":[68],"select":[72],"classifier":[74],"model":[75],"from":[76],"every":[77],"cluster":[78],"make":[80],"up":[81],"membership":[84],"learning.":[88],"Finally,":[89],"performance":[93,104],"by":[97],"vote":[99],"fused":[100],"compare":[103],"bagging":[106],"adaboost":[108],"methods.":[109]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}