{"id":"https://openalex.org/W2240478124","doi":"https://doi.org/10.1109/icnc.2015.7377969","title":"Learning performance of multi-class support vector machines based on Markov sampling","display_name":"Learning performance of multi-class support vector machines based on Markov sampling","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2240478124","doi":"https://doi.org/10.1109/icnc.2015.7377969","mag":"2240478124"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2015.7377969","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2015.7377969","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 11th International Conference on Natural Computation (ICNC)","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/A5100759651","display_name":"Jie Xu","orcid":"https://orcid.org/0000-0001-8238-9344"},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Xu","raw_affiliation_strings":["Faculty of Computer and Information Engineering, Hubei University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer and Information Engineering, Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078058840","display_name":"Bin Zou","orcid":"https://orcid.org/0000-0002-8649-1538"},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Zou","raw_affiliation_strings":["Faculty of Computer and Information Engineering, Hubei University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer and Information Engineering, Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069810287","display_name":"Hanlei Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanlei Shen","raw_affiliation_strings":["Faculty of Computer and Information Engineering, Hubei University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer and Information Engineering, Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I75900474"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14701667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"388","issue":null,"first_page":"74","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9961000084877014,"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":0.9961000084877014,"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/T12676","display_name":"Machine Learning and ELM","score":0.9897000193595886,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9839000105857849,"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/support-vector-machine","display_name":"Support vector machine","score":0.7580624222755432},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6659808158874512},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5934845805168152},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5907204151153564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5812996029853821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.570053219795227},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5414355993270874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3468434810638428}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7580624222755432},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6659808158874512},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5934845805168152},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5907204151153564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5812996029853821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.570053219795227},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5414355993270874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3468434810638428},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc.2015.7377969","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2015.7377969","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 11th International Conference on Natural Computation (ICNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W34176136","https://openalex.org/W1511018260","https://openalex.org/W1963546116","https://openalex.org/W1995713768","https://openalex.org/W2001960189","https://openalex.org/W2020999234","https://openalex.org/W2021440127","https://openalex.org/W2023530265","https://openalex.org/W2046464909","https://openalex.org/W2058402854","https://openalex.org/W2061626571","https://openalex.org/W2066982195","https://openalex.org/W2073522055","https://openalex.org/W2075672181","https://openalex.org/W2078432849","https://openalex.org/W2084028092","https://openalex.org/W2108186573","https://openalex.org/W2110652811","https://openalex.org/W2124101897","https://openalex.org/W2137690105","https://openalex.org/W2142563104","https://openalex.org/W2147303334","https://openalex.org/W2148603752","https://openalex.org/W2153104898","https://openalex.org/W2168228682","https://openalex.org/W2172000360","https://openalex.org/W2273260097","https://openalex.org/W2402905182","https://openalex.org/W3147086063","https://openalex.org/W4312326823","https://openalex.org/W6630446082","https://openalex.org/W7071374342"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W1980100242","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W4315815996"],"abstract_inverted_index":{"SVM":[0,28],"was":[1],"originally":[2],"introduced":[3],"for":[4,70],"classification":[5,36,44,71],"problem":[6,37],"with":[7,46,72,108,130],"two":[8,47],"class":[9,48],"under":[10],"the":[11,14,34,51,56,65,79,97,101,122,126],"condition":[12],"that":[13,121,137],"input":[15],"samples":[16],"are":[17],"drawn":[18],"independent":[19],"and":[20,55,78,95],"identically":[21],"distributed":[22],"(i.i.d.)":[23],"from":[24],"a":[25,40,85],"given":[26],"data.":[27],"had":[29],"been":[30],"considered":[31],"to":[32],"research":[33,64],"multi-class":[35,66,88,106,128],"by":[38],"solving":[39],"series":[41],"of":[42,104,125,138],"b":[43],"problems":[45],"such":[49],"as":[50],"\u201cone-against-one\u201d":[52],"(OAO)":[53],"algorithm":[54,90],"\u201cone-against-all\u201d":[57],"(OAA)":[58],"algorithm.":[59],"In":[60],"this":[61],"text,":[62],"we":[63],"support":[67],"vector":[68],"machine":[69],"based":[73,91,112],"on":[74,92,100,113],"Markov":[75,93,109,131],"selective":[76,110,132],"sampling":[77,94,111,133],"OAO":[80,87,105,127],"method.":[81],"We":[82],"first":[83],"introduce":[84],"new":[86],"SVMC":[89,107,129],"give":[96],"experimental":[98,118],"researchs":[99,119],"learning":[102,123],"ability":[103],"real-world":[114],"data":[115],"sets.":[116],"These":[117],"indicate":[120],"performance":[124],"is":[134],"better":[135],"than":[136],"random":[139],"sampling.":[140]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
