{"id":"https://openalex.org/W2112374302","doi":"https://doi.org/10.1109/ijcnn.2009.5178694","title":"MultiLogistic Regression using Initial and Radial Basis Function covariates","display_name":"MultiLogistic Regression using Initial and Radial Basis Function covariates","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2112374302","doi":"https://doi.org/10.1109/ijcnn.2009.5178694","mag":"2112374302"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2009.5178694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","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/A5063964437","display_name":"Pedro Antonio Guti\u00e9rrez","orcid":"https://orcid.org/0000-0002-2657-776X"},"institutions":[{"id":"https://openalex.org/I53110688","display_name":"University of C\u00f3rdoba","ror":"https://ror.org/05yc77b46","country_code":"ES","type":"education","lineage":["https://openalex.org/I53110688"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Pedro Antonio Gutierrez","raw_affiliation_strings":["Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Cordoba, Spain","Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, Albert Einstein building, 3rd floor, 14071, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Cordoba, Spain","institution_ids":["https://openalex.org/I53110688"]},{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, Albert Einstein building, 3rd floor, 14071, Spain","institution_ids":["https://openalex.org/I53110688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086980043","display_name":"C\u00e9sar Herv\u00e1s\u2010Mart\u00ednez","orcid":"https://orcid.org/0000-0003-4564-1816"},"institutions":[{"id":"https://openalex.org/I53110688","display_name":"University of C\u00f3rdoba","ror":"https://ror.org/05yc77b46","country_code":"ES","type":"education","lineage":["https://openalex.org/I53110688"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Cesar Hervas-Martinez","raw_affiliation_strings":["Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Cordoba, Spain","Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, Albert Einstein building, 3rd floor, 14071, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Cordoba, Spain","institution_ids":["https://openalex.org/I53110688"]},{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, Albert Einstein building, 3rd floor, 14071, Spain","institution_ids":["https://openalex.org/I53110688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044197587","display_name":"Francisco Jos\u00e9 Mart\u00ednez-Estudillo","orcid":"https://orcid.org/0000-0002-4213-0140"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Francisco J. Martinez-Estudillo","raw_affiliation_strings":["Department of Management and Quantitative Methods, ETEA, Cordoba, Spain","Department of Management and Quantitative Methods, ETEA, Escritor Castilla Aguayo 4, 14004 - C\u00f3rdoba, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Management and Quantitative Methods, ETEA, Cordoba, Spain","institution_ids":[]},{"raw_affiliation_string":"Department of Management and Quantitative Methods, ETEA, Escritor Castilla Aguayo 4, 14004 - C\u00f3rdoba, Spain","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050268688","display_name":"Juan Carlos Fern\u00e1ndez Fern\u00e1ndez","orcid":"https://orcid.org/0000-0001-8849-6036"},"institutions":[{"id":"https://openalex.org/I53110688","display_name":"University of C\u00f3rdoba","ror":"https://ror.org/05yc77b46","country_code":"ES","type":"education","lineage":["https://openalex.org/I53110688"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan Carlos Fernandez","raw_affiliation_strings":["Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Cordoba, Spain","Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, Albert Einstein building, 3rd floor, 14071, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Cordoba, Spain","institution_ids":["https://openalex.org/I53110688"]},{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, Albert Einstein building, 3rd floor, 14071, Spain","institution_ids":["https://openalex.org/I53110688"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5063964437"],"corresponding_institution_ids":["https://openalex.org/I53110688"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11765007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"220","issue":null,"first_page":"1067","last_page":"1074"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9936000108718872,"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/T10320","display_name":"Neural Networks and Applications","score":0.9936000108718872,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9908000230789185,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9889000058174133,"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/covariate","display_name":"Covariate","score":0.7174054980278015},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.6615576148033142},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5857839584350586},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5384820103645325},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48517900705337524},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4787166118621826},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4761759638786316},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4723854064941406},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.42737361788749695},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.41166001558303833},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4103237986564636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3586594760417938},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3427582383155823},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2562137842178345}],"concepts":[{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.7174054980278015},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.6615576148033142},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5857839584350586},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5384820103645325},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48517900705337524},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4787166118621826},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4761759638786316},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4723854064941406},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.42737361788749695},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.41166001558303833},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4103237986564636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3586594760417938},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3427582383155823},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2562137842178345},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2009.5178694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","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":37,"referenced_works":["https://openalex.org/W291003596","https://openalex.org/W969985410","https://openalex.org/W1480376833","https://openalex.org/W1480487340","https://openalex.org/W1506806321","https://openalex.org/W1514875444","https://openalex.org/W1570448133","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1770825568","https://openalex.org/W1978479174","https://openalex.org/W1981039744","https://openalex.org/W1997917263","https://openalex.org/W2016944307","https://openalex.org/W2024046085","https://openalex.org/W2024060531","https://openalex.org/W2034766165","https://openalex.org/W2061554433","https://openalex.org/W2085232632","https://openalex.org/W2090901734","https://openalex.org/W2094538992","https://openalex.org/W2106393550","https://openalex.org/W2109527845","https://openalex.org/W2113442785","https://openalex.org/W2134514463","https://openalex.org/W2135346934","https://openalex.org/W2138784882","https://openalex.org/W2153635508","https://openalex.org/W2162635690","https://openalex.org/W2171277043","https://openalex.org/W2966207845","https://openalex.org/W3120421331","https://openalex.org/W3120740533","https://openalex.org/W3173138228","https://openalex.org/W4205210034","https://openalex.org/W4256451422","https://openalex.org/W6634094483"],"related_works":["https://openalex.org/W2985746494","https://openalex.org/W4206042385","https://openalex.org/W2511384863","https://openalex.org/W2080773131","https://openalex.org/W2096089271","https://openalex.org/W31220157","https://openalex.org/W2288557197","https://openalex.org/W4233024177","https://openalex.org/W2101914902","https://openalex.org/W3174613421"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,41,47,86,96],"hybrid":[4],"multilogistic":[5,8,97,112,166,202],"model,":[6],"named":[7],"regression":[9,98,113,167,203],"using":[10,149],"initial":[11,121,172],"and":[12,53,122,126,134,184,205,213],"radial":[13],"basis":[14],"function":[15],"covariates":[16,124],"(MLRIRBF).":[17],"The":[18,144,159,191],"process":[19],"for":[20,209],"obtaining":[21],"the":[22,54,59,66,70,75,78,82,92,132,164,171,176,180,200,206,215,223],"coefficients":[23,93],"is":[24,36,62,147],"carried":[25],"out":[26],"in":[27,81,138,227],"several":[28],"steps.":[29],"First,":[30],"an":[31,139],"evolutionary":[32],"programming":[33],"(EP)":[34],"algorithm":[35,182],"applied,":[37,116],"aimed":[38],"to":[39,175,185,196,222],"produce":[40],"RBF":[42,51,123],"neural":[43],"network":[44],"(RBFNN)":[45],"with":[46,95,163],"reduced":[48],"number":[49],"of":[50,69,77,225],"transformations":[52,68],"simplest":[55],"structure":[56],"possible.":[57],"Then,":[58],"input":[60,71,104,173],"space":[61],"transformed":[63,103],"by":[64,74,179],"adding":[65],"nonlinear":[67],"variables":[72],"given":[73],"RBFs":[76],"best":[79],"individual":[80],"last":[83],"generation.":[84],"Finally,":[85],"maximum":[87],"likelihood":[88],"optimization":[89],"method":[90,208],"determines":[91],"associated":[94],"model":[99,133],"built":[100],"on":[101],"this":[102,107],"space.":[105],"In":[106],"final":[108],"step,":[109],"two":[110],"different":[111],"algorithms":[114],"are":[115,161,194],"one":[117,128],"that":[118,129],"considers":[119],"all":[120,211,228],"(MLRIRBF)":[125],"another":[127],"incrementally":[130],"constructs":[131],"applies":[135],"cross-validation,":[136],"resulting":[137],"automatic":[140],"covariate":[141],"selection":[142],"(MLRIRBF*).":[143],"methodology":[145],"proposed":[146],"tested":[148],"six":[150],"benchmark":[151],"classification":[152],"problems":[153],"from":[154],"well-known":[155],"machine":[156,188],"learning":[157,189],"problems.":[158],"results":[160],"compared":[162,221],"corresponding":[165,201],"methodologies":[168,204],"applied":[169],"over":[170],"space,":[174],"RBFNNs":[177],"obtained":[178],"EP":[181],"(RBFEP)":[183],"other":[186],"competitive":[187],"techniques.":[190],"MLRIRBF*":[192],"models":[193],"found":[195],"be":[197],"better":[198],"than":[199],"RBFEP":[207],"almost":[210],"datasets,":[212],"obtain":[214],"highest":[216],"mean":[217],"accuracy":[218],"rank":[219],"when":[220],"rest":[224],"methods":[226],"datasets.":[229]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}