{"id":"https://openalex.org/W397830089","doi":"https://doi.org/10.1109/tnnls.2015.2429711","title":"Data Generators for Learning Systems Based on RBF Networks","display_name":"Data Generators for Learning Systems Based on RBF Networks","publication_year":2015,"publication_date":"2015-05-22","ids":{"openalex":"https://openalex.org/W397830089","doi":"https://doi.org/10.1109/tnnls.2015.2429711","mag":"397830089","pmid":"https://pubmed.ncbi.nlm.nih.gov/26011896"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2015.2429711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2015.2429711","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1403.7308","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020021079","display_name":"Marko Robnik\u2010\u0160ikonja","orcid":"https://orcid.org/0000-0002-1232-3320"},"institutions":[{"id":"https://openalex.org/I153976015","display_name":"University of Ljubljana","ror":"https://ror.org/05njb9z20","country_code":"SI","type":"education","lineage":["https://openalex.org/I153976015"]}],"countries":["SI"],"is_corresponding":true,"raw_author_name":"Marko Robnik-Sikonja","raw_affiliation_strings":["Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I153976015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5020021079"],"corresponding_institution_ids":["https://openalex.org/I153976015"],"apc_list":null,"apc_paid":null,"fwci":5.3547,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.95594656,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"27","issue":"5","first_page":"926","last_page":"938"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T10057","display_name":"Face and Expression Recognition","score":0.9898999929428101,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9894000291824341,"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/overfitting","display_name":"Overfitting","score":0.818676769733429},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7520931363105774},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6269569396972656},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6212546229362488},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6062328219413757},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5295753479003906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5266168713569641},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5191327929496765},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.462448388338089},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.45098623633384705},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35385239124298096},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.29003167152404785}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.818676769733429},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520931363105774},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6269569396972656},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6212546229362488},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6062328219413757},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5295753479003906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5266168713569641},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5191327929496765},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.462448388338089},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.45098623633384705},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35385239124298096},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29003167152404785},{"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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2015.2429711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2015.2429711","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:26011896","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26011896","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:arXiv.org:1403.7308","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1403.7308","pdf_url":"https://arxiv.org/pdf/1403.7308","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1403.7308","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1403.7308","pdf_url":"https://arxiv.org/pdf/1403.7308","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1095062678","display_name":null,"funder_award_id":"604102","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1513618424","https://openalex.org/W1607735679","https://openalex.org/W1817040532","https://openalex.org/W1990694356","https://openalex.org/W2033403400","https://openalex.org/W2034489756","https://openalex.org/W2036045975","https://openalex.org/W2040622182","https://openalex.org/W2042284615","https://openalex.org/W2051327168","https://openalex.org/W2055913343","https://openalex.org/W2064186732","https://openalex.org/W2068773963","https://openalex.org/W2081913622","https://openalex.org/W2085783217","https://openalex.org/W2092783572","https://openalex.org/W2093022009","https://openalex.org/W2102073628","https://openalex.org/W2113054345","https://openalex.org/W2119436275","https://openalex.org/W2159798994","https://openalex.org/W2167025280","https://openalex.org/W2167277498","https://openalex.org/W2170219541","https://openalex.org/W2171277043","https://openalex.org/W2244624726","https://openalex.org/W2271397697","https://openalex.org/W2615953416","https://openalex.org/W2999729612","https://openalex.org/W3120740533","https://openalex.org/W4235169531","https://openalex.org/W4241861175","https://openalex.org/W4251263574","https://openalex.org/W6675376746"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W3009056573","https://openalex.org/W4297676672","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4288087796"],"abstract_inverted_index":{"There":[0],"are":[1],"plenty":[2],"of":[3,17,33,41,54,69,94,103,121,173],"problems":[4],"where":[5],"the":[6,24,29,39,87,92,95,100,104,122,142,150,166,174,178,189],"data":[7,19,35,46,85,133,146,176,184],"available":[8],"is":[9,59,192],"scarce":[10],"and":[11,31,38,50,109,114,144,147,158,186],"expensive.":[12],"We":[13,161],"propose":[14],"a":[15,79,127,138],"generator":[16,58,124],"semiartificial":[18],"with":[20],"similar":[21],"properties":[22,102],"to":[23,82,177],"original":[25,143],"data,":[26,97,106],"which":[27,66],"enables":[28],"development":[30,157],"testing":[32],"different":[34,171],"mining":[36],"algorithms":[37],"optimization":[40],"their":[42],"parameters.":[43],"The":[44,56,135],"generated":[45,96,105,145,175],"allow":[47],"large-scale":[48],"experimentation":[49],"simulations":[51],"without":[52],"danger":[53],"overfitting.":[55],"proposed":[57,123,190],"based":[60],"on":[61,182],"radial":[62],"basis":[63],"function":[64],"networks,":[65],"learn":[67],"sets":[68],"Gaussian":[70,73],"kernels.":[71],"These":[72],"kernels":[74],"can":[75,152],"be":[76,153],"used":[77],"in":[78,155,165],"generative":[80],"mode":[81],"generate":[83],"new":[84],"from":[86],"same":[88],"distributions.":[89],"To":[90,118],"assess":[91],"quality":[93],"we":[98,125],"evaluated":[99],"statistical":[101],"structural":[107],"similarity,":[108],"predictive":[110],"similarity":[111,140],"using":[112,131],"supervised":[113],"unsupervised":[115],"learning":[116],"techniques.":[117],"determine":[119],"usability":[120],"conducted":[126],"large":[128],"scale":[129],"evaluation":[130],"51":[132],"sets.":[134],"results":[136],"show":[137],"considerable":[139],"between":[141],"indicate":[148],"that":[149],"method":[151],"useful":[154],"several":[156],"simulation":[159],"scenarios.":[160],"analyze":[162],"possible":[163],"improvements":[164],"classification":[167],"performance":[168,181],"by":[169],"adding":[170],"amounts":[172],"training":[179],"set,":[180],"high-dimensional":[183],"sets,":[185],"conditions":[187],"when":[188],"approach":[191],"successful.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}