{"id":"https://openalex.org/W2314715715","doi":"https://doi.org/10.3233/ifs-151743","title":"Least squares support vector machine with parametric margin for binary classification1","display_name":"Least squares support vector machine with parametric margin for binary classification1","publication_year":2016,"publication_date":"2016-04-02","ids":{"openalex":"https://openalex.org/W2314715715","doi":"https://doi.org/10.3233/ifs-151743","mag":"2314715715"},"language":"en","primary_location":{"id":"doi:10.3233/ifs-151743","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ifs-151743","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://ir.ipe.ac.cn/handle/122111/21009","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051273783","display_name":"Zhixia Yang","orcid":"https://orcid.org/0000-0003-0446-4278"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]},{"id":"https://openalex.org/I4210133325","display_name":"Institute of Process Engineering","ror":"https://ror.org/03j4x9j18","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210133325"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhixia Yang","raw_affiliation_strings":["College of Mathematics and Systems Science, Xinjiang University, Urumuqi, P.R.China","State Key Lab of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Science, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Systems Science, Xinjiang University, Urumuqi, P.R.China","institution_ids":["https://openalex.org/I96908189"]},{"raw_affiliation_string":"State Key Lab of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Science, Beijing, China","institution_ids":["https://openalex.org/I4210133325"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056293526","display_name":"Zhe Zhou","orcid":"https://orcid.org/0000-0002-0445-2560"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Zhou","raw_affiliation_strings":["College of Mathematics and Systems Science, Xinjiang University, Urumuqi, P.R.China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Systems Science, Xinjiang University, Urumuqi, P.R.China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034372090","display_name":"Yao\u2010Lin Jiang","orcid":"https://orcid.org/0000-0002-5541-1136"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaolin Jiang","raw_affiliation_strings":["College of Mathematics and Systems Science, Xinjiang University, Urumuqi, P.R.China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Systems Science, Xinjiang University, Urumuqi, P.R.China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051273783"],"corresponding_institution_ids":["https://openalex.org/I4210133325","https://openalex.org/I96908189"],"apc_list":null,"apc_paid":null,"fwci":0.167,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.53506637,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"30","issue":"5","first_page":"2897","last_page":"2904"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987999796867371,"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":0.9987999796867371,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"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":0.812781810760498},{"id":"https://openalex.org/keywords/hyperplane","display_name":"Hyperplane","score":0.7460736036300659},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6914525628089905},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.6436843872070312},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5948259830474854},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5715687870979309},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5558197498321533},{"id":"https://openalex.org/keywords/least-squares-support-vector-machine","display_name":"Least squares support vector machine","score":0.5481626391410828},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.52625572681427},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.5167809724807739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49879884719848633},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49208253622055054},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4865399897098541},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4785892963409424},{"id":"https://openalex.org/keywords/heteroscedasticity","display_name":"Heteroscedasticity","score":0.47488826513290405},{"id":"https://openalex.org/keywords/structured-support-vector-machine","display_name":"Structured support vector machine","score":0.47462427616119385},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.41938018798828125},{"id":"https://openalex.org/keywords/relevance-vector-machine","display_name":"Relevance vector machine","score":0.41469675302505493},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3675835132598877},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22602632641792297},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14417871832847595}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.812781810760498},{"id":"https://openalex.org/C68693459","wikidata":"https://www.wikidata.org/wiki/Q657586","display_name":"Hyperplane","level":2,"score":0.7460736036300659},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6914525628089905},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6436843872070312},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5948259830474854},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5715687870979309},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5558197498321533},{"id":"https://openalex.org/C145828037","wikidata":"https://www.wikidata.org/wiki/Q17086219","display_name":"Least squares support vector machine","level":3,"score":0.5481626391410828},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.52625572681427},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.5167809724807739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49879884719848633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49208253622055054},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4865399897098541},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4785892963409424},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.47488826513290405},{"id":"https://openalex.org/C125168437","wikidata":"https://www.wikidata.org/wiki/Q7625184","display_name":"Structured support vector machine","level":3,"score":0.47462427616119385},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.41938018798828125},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.41469675302505493},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3675835132598877},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22602632641792297},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14417871832847595},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","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/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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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":2,"locations":[{"id":"doi:10.3233/ifs-151743","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ifs-151743","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"},{"id":"pmh:oai:ir.ipe.ac.cn:122111/21009","is_oa":true,"landing_page_url":"http://ir.ipe.ac.cn/handle/122111/21009","pdf_url":null,"source":{"id":"https://openalex.org/S4306400543","display_name":"CAS OpenIR (Chinese Academy of Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I19820366","host_organization_name":"Chinese Academy of Sciences","host_organization_lineage":["https://openalex.org/I19820366"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:ir.ipe.ac.cn:122111/21009","is_oa":true,"landing_page_url":"http://ir.ipe.ac.cn/handle/122111/21009","pdf_url":null,"source":{"id":"https://openalex.org/S4306400543","display_name":"CAS OpenIR (Chinese Academy of Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I19820366","host_organization_name":"Chinese Academy of Sciences","host_organization_lineage":["https://openalex.org/I19820366"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1490760466","https://openalex.org/W1530144005","https://openalex.org/W1596717185","https://openalex.org/W2032023325","https://openalex.org/W2036350498","https://openalex.org/W2038445713","https://openalex.org/W2042561770","https://openalex.org/W2084812512","https://openalex.org/W2090089568","https://openalex.org/W2119821739","https://openalex.org/W2132425109","https://openalex.org/W2156909104","https://openalex.org/W2170860445","https://openalex.org/W2496585406","https://openalex.org/W2982720039","https://openalex.org/W3150204026","https://openalex.org/W4239510810","https://openalex.org/W4249465073"],"related_works":["https://openalex.org/W2122277321","https://openalex.org/W2049586051","https://openalex.org/W1678040990","https://openalex.org/W2769345709","https://openalex.org/W2178308471","https://openalex.org/W2023602538","https://openalex.org/W2315850941","https://openalex.org/W2350916155","https://openalex.org/W2544750528","https://openalex.org/W2071357642"],"abstract_inverted_index":{"In":[0],"this":[1,52],"paper,":[2],"we":[3],"propose":[4],"a":[5,23],"least":[6],"squares":[7],"support":[8],"vector":[9],"machine":[10],"with":[11,35,58],"parametric":[12],"margin":[13],"(Par-LSSVM)":[14],"for":[15,79],"binary":[16,80],"classification,":[17],"which":[18],"only":[19],"needs":[20],"to":[21,31,42],"solve":[22],"system":[24],"of":[25,56],"linear":[26],"equation.":[27],"Par-LSSVM":[28,54],"is":[29],"able":[30],"handle":[32],"the":[33,39,43,48],"datasets":[34,71],"heteroscedastic":[36],"noise.":[37],"And":[38],"closer":[40],"hyperplane":[41],"test":[44],"data":[45],"point":[46],"gives":[47],"class":[49],"label,":[50],"and":[51,69],"makes":[53],"capable":[55],"dealing":[57],"\u201cCross":[59],"Planes\u201d":[60],"datasets.":[61],"The":[62],"experimental":[63],"results":[64],"on":[65],"several":[66],"artificial,":[67],"benchmark":[68],"USPS":[70],"indicate":[72],"that":[73],"our":[74],"proposed":[75],"algorithm":[76],"outperforms":[77],"Par-\u03bd-SVM":[78],"classification":[81],"problem.":[82]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}