{"id":"https://openalex.org/W2156969234","doi":"https://doi.org/10.1109/ijcnn.2008.4634028","title":"Extreme learning machine for multi-categories classification applications","display_name":"Extreme learning machine for multi-categories classification applications","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2156969234","doi":"https://doi.org/10.1109/ijcnn.2008.4634028","mag":"2156969234"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4634028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5033905708","display_name":"Hai-Jun Rong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hai-Jun Rong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061746912","display_name":"Guang-Bin Huang","orcid":"https://orcid.org/0000-0002-2480-4965"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guang-Bin Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068243197","display_name":"Yew-Soon Ong","orcid":"https://orcid.org/0000-0002-4480-169X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yew-Soon Ong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1709","last_page":"1713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"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/T12676","display_name":"Machine Learning and ELM","score":1.0,"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/T10062","display_name":"MicroRNA in disease regulation","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10773","display_name":"Extracellular vesicles in disease","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.9614877700805664},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7129714488983154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6964589357376099},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.669770359992981},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5606294870376587},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5431567430496216},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4642553925514221},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4625287652015686},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4232105612754822},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.29958444833755493},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26393646001815796},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16597548127174377}],"concepts":[{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.9614877700805664},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7129714488983154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6964589357376099},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.669770359992981},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5606294870376587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5431567430496216},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4642553925514221},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4625287652015686},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4232105612754822},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.29958444833755493},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26393646001815796},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16597548127174377},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2008.4634028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1521849663","https://openalex.org/W1588401315","https://openalex.org/W1968918799","https://openalex.org/W2034223886","https://openalex.org/W2040604977","https://openalex.org/W2061065224","https://openalex.org/W2084812512","https://openalex.org/W2108223084","https://openalex.org/W2110158084","https://openalex.org/W2111072639","https://openalex.org/W2121562849","https://openalex.org/W2122040390","https://openalex.org/W2134603844","https://openalex.org/W2140702676","https://openalex.org/W2141695047","https://openalex.org/W2147243899","https://openalex.org/W2161055889","https://openalex.org/W2163572752","https://openalex.org/W2260859552","https://openalex.org/W4285719527","https://openalex.org/W6635310694","https://openalex.org/W6678129794"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2968645206","https://openalex.org/W3189276259","https://openalex.org/W4382934300","https://openalex.org/W2121061354","https://openalex.org/W4285388059"],"abstract_inverted_index":{"In":[0,62,113],"the":[1,3,36,45,67,82,109,124,129],"paper,":[2],"multi-class":[4,37,68,93],"pattern":[5,85,130],"classification":[6],"using":[7,32,44,91],"extreme":[8],"learning":[9],"machine":[10],"(ELM)":[11],"is":[12,16,39,70,79,89,133],"studied.":[13],"The":[14],"study":[15],"based":[17],"on":[18],"either":[19],"a":[20,27,63],"series":[21],"of":[22,75,84],"ELM":[23,29,34,65,111,126],"binary":[24,33],"classifiers":[25],"or":[26,119],"single":[28,64,110,125],"classifier.":[30,112],"When":[31],"classifiers,":[35],"problem":[38,43,69],"decomposed":[40],"into":[41],"two-class":[42],"one-against-all":[46],"(OAA)":[47],"and":[48,57,96,102],"one-against-one":[49],"(OAO)":[50],"schemes,":[51],"which":[52,78],"are":[53],"named":[54],"as":[55],"ELM-OAA":[56,101],"ELM-OAO":[58,103,115],"respectively":[59],"for":[60],"brevity.":[61],"classifier,":[66],"implemented":[71],"with":[72],"an":[73],"architecture":[74],"multi-output":[76],"nodes":[77,107],"equal":[80],"to":[81],"number":[83],"classes.":[86],"Their":[87],"performance":[88],"evaluated":[90],"some":[92],"benchmark":[94],"problems":[95],"simulation":[97],"results":[98],"show":[99],"that":[100],"requires":[104],"fewer":[105],"hidden":[106],"than":[108,123,136],"addition":[114],"usually":[116],"has":[117],"similar":[118],"less":[120],"computation":[121],"burden":[122],"classifier":[127],"when":[128],"class":[131],"labels":[132],"not":[134],"larger":[135],"10.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
