{"id":"https://openalex.org/W2012312891","doi":"https://doi.org/10.1145/2063576.2063678","title":"Designing an ensemble classifier over subspace classifiers using iterative convergence routine","display_name":"Designing an ensemble classifier over subspace classifiers using iterative convergence routine","publication_year":2011,"publication_date":"2011-10-24","ids":{"openalex":"https://openalex.org/W2012312891","doi":"https://doi.org/10.1145/2063576.2063678","mag":"2012312891"},"language":"en","primary_location":{"id":"doi:10.1145/2063576.2063678","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2063576.2063678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM international conference on Information and knowledge management","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/A5017540117","display_name":"Bhanukiran Vinzamuri","orcid":"https://orcid.org/0000-0003-2651-8628"},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Bhanukiran Vinzamuri","raw_affiliation_strings":["International Institute of Information Technology, Hyderabad, India","[International Institute of Information Technology Hyderabad, India]"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad, India","institution_ids":["https://openalex.org/I64189192"]},{"raw_affiliation_string":"[International Institute of Information Technology Hyderabad, India]","institution_ids":["https://openalex.org/I64189192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088255710","display_name":"Kamalakar Karlapalem","orcid":"https://orcid.org/0000-0003-2528-7979"},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kamalakar Karlapalem","raw_affiliation_strings":["International Institute of Information Technology, Hyderabad, India","[International Institute of Information Technology Hyderabad, India]"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad, India","institution_ids":["https://openalex.org/I64189192"]},{"raw_affiliation_string":"[International Institute of Information Technology Hyderabad, India]","institution_ids":["https://openalex.org/I64189192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017540117"],"corresponding_institution_ids":["https://openalex.org/I64189192"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0860351,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"693","last_page":"698"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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":0.9990000128746033,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9973000288009644,"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":0.9954000115394592,"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":0.9298843145370483},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7608911991119385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7050904035568237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6863277554512024},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6707748770713806},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6059151887893677},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5764278769493103},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5589526891708374},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5369489192962646},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.5048978924751282},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4337750971317291},{"id":"https://openalex.org/keywords/quadratic-classifier","display_name":"Quadratic classifier","score":0.41023680567741394},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36232227087020874},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19843724370002747}],"concepts":[{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.9298843145370483},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7608911991119385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7050904035568237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6863277554512024},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6707748770713806},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6059151887893677},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5764278769493103},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5589526891708374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5369489192962646},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.5048978924751282},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4337750971317291},{"id":"https://openalex.org/C52620605","wikidata":"https://www.wikidata.org/wiki/Q7268357","display_name":"Quadratic classifier","level":3,"score":0.41023680567741394},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36232227087020874},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19843724370002747},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2063576.2063678","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2063576.2063678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM international conference on Information and knowledge management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320308943","display_name":"Microsoft Research","ror":"https://ror.org/00d0nc645"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W60432172","https://openalex.org/W122801842","https://openalex.org/W1534477342","https://openalex.org/W2031079940","https://openalex.org/W2112076978","https://openalex.org/W2117355841","https://openalex.org/W2132549764","https://openalex.org/W2135105223","https://openalex.org/W2140190241","https://openalex.org/W2158275940","https://openalex.org/W2293273145","https://openalex.org/W2429914308","https://openalex.org/W2911964244","https://openalex.org/W6676769703","https://openalex.org/W6680704940"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W4294291164","https://openalex.org/W3172436493","https://openalex.org/W1887135636","https://openalex.org/W4287164812","https://openalex.org/W2143234973","https://openalex.org/W2386063599","https://openalex.org/W1975884855"],"abstract_inverted_index":{"There":[0],"can":[1],"be":[2],"multiple":[3,14],"classifiers":[4,15,30],"for":[5,87],"a":[6,102],"given":[7],"data":[8,52],"set.":[9],"One":[10],"way":[11],"to":[12,17,36,64,108],"generate":[13,28],"is":[16,101],"use":[18],"subspaces":[19],"of":[20,46,68,83],"the":[21,44,66,81,84],"attribute":[22],"sets.":[23],"In":[24],"this":[25],"paper,":[26],"we":[27],"subspace":[29],"by":[31],"an":[32,38],"iterative":[33],"convergence":[34],"routine":[35],"build":[37],"ensemble":[39,99],"classifier.":[40],"Experimental":[41],"evaluation":[42],"covers":[43],"cases":[45],"both":[47],"labelled":[48],"and":[49,79],"unlabelled":[50],"(blind)":[51],"separately.":[53],"We":[54,76],"evaluate":[55],"our":[56,69,98],"approach":[57,70],"on":[58],"many":[59],"benchmark":[60],"UC":[61],"Irvine":[62],"datasets":[63],"assess":[65],"robustness":[67],"with":[71],"varying":[72],"induced":[73],"noise":[74],"levels.":[75],"explicitly":[77],"compare":[78],"present":[80],"utility":[82],"clusterings":[85],"generated":[86],"classification":[88,111],"using":[89],"several":[90],"diverse":[91],"clustering":[92],"dissimilarity":[93],"metrics.":[94],"Results":[95],"show":[96],"that":[97],"classifier":[100,105],"more":[103],"robust":[104],"in":[106],"comparison":[107],"different":[109],"multi-class":[110],"approaches.":[112]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}