{"id":"https://openalex.org/W2056224615","doi":"https://doi.org/10.1109/ijcnn.2013.6706910","title":"Active testing for SVM parameter selection","display_name":"Active testing for SVM parameter selection","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2056224615","doi":"https://doi.org/10.1109/ijcnn.2013.6706910","mag":"2056224615"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2013.6706910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6706910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","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/A5078294323","display_name":"P\u00e9ricles Miranda","orcid":"https://orcid.org/0000-0002-5767-7544"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Pericles B. C. Miranda","raw_affiliation_strings":["Centro de Inform\u00e1tica, Universidade Federal de Pernambuco","Centro de Inf., Univ. Fed. de Pernambuco, Recife, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco","institution_ids":["https://openalex.org/I25112270"]},{"raw_affiliation_string":"Centro de Inf., Univ. Fed. de Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083998049","display_name":"Ricardo B. C. Prud\u00eancio","orcid":"https://orcid.org/0000-0001-7084-1233"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ricardo B. C. Prudencio","raw_affiliation_strings":["Centro de Inform\u00e1tica, Universidade Federal de Pernambuco","Centro de Inf., Univ. Fed. de Pernambuco, Recife, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco","institution_ids":["https://openalex.org/I25112270"]},{"raw_affiliation_string":"Centro de Inf., Univ. Fed. de Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I25112270"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25112270"],"apc_list":null,"apc_paid":null,"fwci":0.2288,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.48310798,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.986299991607666,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9764999747276306,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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":0.7436798810958862},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7094700336456299},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6709189414978027},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6341931819915771},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6064053773880005},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.558698296546936},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5234315395355225},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5233318209648132},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.5194680094718933},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5022308826446533},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47803956270217896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15113455057144165},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07071083784103394}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7436798810958862},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7094700336456299},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6709189414978027},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6341931819915771},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6064053773880005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.558698296546936},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5234315395355225},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5233318209648132},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.5194680094718933},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5022308826446533},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47803956270217896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15113455057144165},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07071083784103394},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2013.6706910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6706910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W176885764","https://openalex.org/W178592443","https://openalex.org/W1489517264","https://openalex.org/W1718583055","https://openalex.org/W1925504357","https://openalex.org/W1969163824","https://openalex.org/W1989048657","https://openalex.org/W2000703693","https://openalex.org/W2063270381","https://openalex.org/W2066496894","https://openalex.org/W2089213632","https://openalex.org/W2101578906","https://openalex.org/W2109943925","https://openalex.org/W2118286367","https://openalex.org/W2138882494","https://openalex.org/W2143628522","https://openalex.org/W2143677699","https://openalex.org/W2152382740","https://openalex.org/W2158001550","https://openalex.org/W2159214028","https://openalex.org/W2159524357","https://openalex.org/W2165607334","https://openalex.org/W2168031673","https://openalex.org/W2626984672","https://openalex.org/W3120740533","https://openalex.org/W4231214146","https://openalex.org/W4235116485","https://openalex.org/W6637436003","https://openalex.org/W6677537363","https://openalex.org/W6684802269","https://openalex.org/W6740135727"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2807634898","https://openalex.org/W1692008701","https://openalex.org/W2942366970","https://openalex.org/W2597588799","https://openalex.org/W2550904580","https://openalex.org/W2963653239"],"abstract_inverted_index":{"The":[0,160],"Support":[1],"Vector":[2],"Machine":[3],"algorithm":[4,20],"is":[5,44],"sensitive":[6],"to":[7,35,57,99,173],"the":[8,19,37,48,51,54,59,77,87,116,124,130,138,142,163],"choice":[9],"of":[10,39,50,103,126,140,165],"parameter":[11,132],"settings.":[12],"If":[13],"these":[14],"are":[15,112],"not":[16],"set":[17],"correctly,":[18],"may":[21],"have":[22],"a":[23,66,73,100],"substandard":[24],"performance.":[25],"It":[26],"has":[27],"been":[28],"shown":[29],"that":[30,168,182],"meta-learning":[31],"can":[32],"be":[33],"used":[34,56],"support":[36],"selection":[38],"SVM":[40,131],"parameters.":[41],"However,":[42],"it":[43,136],"very":[45],"dependent":[46],"on":[47,76,115,137,157,170,184],"quality":[49],"dataset":[52,74,104,175],"and":[53,106,149],"meta-features":[55],"characterize":[58],"dataset.":[60,118],"As":[61],"alternative":[62],"for":[63,129,146],"this":[64,120],"problem,":[65],"recent":[67],"technique":[68],"called":[69],"Active":[70,127,166],"Testing":[71,128,167],"characterized":[72],"based":[75,156],"pairwise":[78],"performance":[79],"differences":[80],"between":[81],"possible":[82],"solutions.":[83],"This":[84],"approach":[85],"selects":[86],"most":[88,113],"useful":[89],"cross-validation":[90,94,171],"tests.":[91],"Each":[92],"new":[93,117],"test":[95,135],"will":[96],"contribute":[97],"information":[98],"better":[101,108,178],"estimate":[102,174],"similarity,":[105],"thus":[107],"predict":[109],"which":[110],"algorithms":[111],"promising":[114],"In":[119],"paper":[121],"we":[122,150],"propose":[123],"application":[125],"problem.":[133],"We":[134],"problem":[139],"setting":[141],"RBF":[143],"kernel":[144],"parameters":[145],"classification":[147],"problems":[148],"compare":[151],"its":[152],"similarity":[153,176],"strategy":[154],"with":[155],"data":[158,185],"characteristics.":[159,186],"results":[161],"showed":[162],"variants":[164],"rely":[169,183],"tests":[172],"provides":[177],"solutions":[179],"than":[180],"those":[181]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}