{"id":"https://openalex.org/W2008757383","doi":"https://doi.org/10.1109/igarss.2010.5649251","title":"An automatic method for selecting the parameter of the RBF kernel function to support vector machines","display_name":"An automatic method for selecting the parameter of the RBF kernel function to support vector machines","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2008757383","doi":"https://doi.org/10.1109/igarss.2010.5649251","mag":"2008757383"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2010.5649251","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2010.5649251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Geoscience and Remote Sensing Symposium","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/A5006434175","display_name":"Cheng\u2010Hsuan Li","orcid":"https://orcid.org/0000-0001-5059-8256"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]},{"id":"https://openalex.org/I34574549","display_name":"National Taichung University of Education","ror":"https://ror.org/006tnfe02","country_code":"TW","type":"education","lineage":["https://openalex.org/I34574549"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Hsuan Li","raw_affiliation_strings":["Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taichung, Taiwan","Institute of Electrical Control Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taichung, Taiwan","institution_ids":["https://openalex.org/I34574549"]},{"raw_affiliation_string":"Institute of Electrical Control Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058936239","display_name":"Chin\u2010Teng Lin","orcid":"https://orcid.org/0000-0001-8371-8197"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chin-Teng Lin","raw_affiliation_strings":["Institute of Electrical Control Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electrical Control Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054302891","display_name":"Bor\u2010Chen Kuo","orcid":"https://orcid.org/0000-0003-1741-2450"},"institutions":[{"id":"https://openalex.org/I34574549","display_name":"National Taichung University of Education","ror":"https://ror.org/006tnfe02","country_code":"TW","type":"education","lineage":["https://openalex.org/I34574549"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Bor-Chen Kuo","raw_affiliation_strings":["Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taichung, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taichung, Taiwan","institution_ids":["https://openalex.org/I34574549"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030622704","display_name":"Hui-Shan Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I34574549","display_name":"National Taichung University of Education","ror":"https://ror.org/006tnfe02","country_code":"TW","type":"education","lineage":["https://openalex.org/I34574549"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hui-Shan Chu","raw_affiliation_strings":["Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taichung, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taichung, Taiwan","institution_ids":["https://openalex.org/I34574549"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9940000176429749,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8224215507507324},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.7262468338012695},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7201682329177856},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.5924133062362671},{"id":"https://openalex.org/keywords/least-squares-support-vector-machine","display_name":"Least squares support vector machine","score":0.5212379097938538},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5026519298553467},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.5002529621124268},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.4996774196624756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4988696575164795},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4848531484603882},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4740804433822632},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.42592653632164},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.41811954975128174},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41267621517181396},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1611265242099762}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8224215507507324},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.7262468338012695},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7201682329177856},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.5924133062362671},{"id":"https://openalex.org/C145828037","wikidata":"https://www.wikidata.org/wiki/Q17086219","display_name":"Least squares support vector machine","level":3,"score":0.5212379097938538},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5026519298553467},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.5002529621124268},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.4996774196624756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4988696575164795},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4848531484603882},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4740804433822632},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.42592653632164},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.41811954975128174},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41267621517181396},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1611265242099762},{"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/igarss.2010.5649251","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2010.5649251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W59495185","https://openalex.org/W628438000","https://openalex.org/W1510073064","https://openalex.org/W1568288633","https://openalex.org/W2035337734","https://openalex.org/W2041657594","https://openalex.org/W2056215075","https://openalex.org/W2099129687","https://openalex.org/W2104269704","https://openalex.org/W2111787810","https://openalex.org/W2114819256","https://openalex.org/W2136251662","https://openalex.org/W2140389641","https://openalex.org/W2151194815","https://openalex.org/W2153635508","https://openalex.org/W2167685974","https://openalex.org/W2475686826","https://openalex.org/W2478493250","https://openalex.org/W3120421331"],"related_works":["https://openalex.org/W4311138679","https://openalex.org/W2384322977","https://openalex.org/W2005311689","https://openalex.org/W2393746448","https://openalex.org/W4211002245","https://openalex.org/W3100948281","https://openalex.org/W2357150443","https://openalex.org/W2101950939","https://openalex.org/W2610404083","https://openalex.org/W1563486225"],"abstract_inverted_index":{"Support":[0],"vector":[1],"machine":[2],"(SVM)":[3],"is":[4,35,81],"one":[5],"of":[6,17,30,57,76],"the":[7,15,23,41,47,52,58,74,77,84,97,104,124],"most":[8],"powerful":[9],"techniques":[10],"for":[11,72,95],"supervised":[12],"classification.":[13],"However,":[14],"performances":[16],"SVMs":[18,106,117],"are":[19],"based":[20],"on":[21],"choosing":[22],"proper":[24,28],"kernel":[25,32,79],"functions":[26],"or":[27,111],"parameters":[29],"a":[31],"function.":[33],"It":[34],"extremely":[36],"time":[37,91],"consuming":[38],"by":[39,99,118],"applying":[40,119],"k-fold":[42,93,120],"cross-validation":[43,94,121],"(CV)":[44],"to":[45,122],"choose":[46],"almost":[48],"best":[49],"parameter.":[50,125],"Nevertheless,":[51],"searching":[53],"range":[54],"and":[55],"fineness":[56],"grid":[59],"method":[60,71],"should":[61],"be":[62],"determined":[63],"in":[64],"advance.":[65],"In":[66,83],"this":[67],"paper,":[68],"an":[69],"automatic":[70],"selecting":[73,96],"parameter":[75,98],"RBF":[78],"function":[80],"proposed.":[82],"experimental":[85],"results,":[86],"it":[87],"costs":[88],"very":[89],"little":[90],"than":[92,116],"our":[100],"proposed":[101],"method.":[102],"Moreover,":[103],"corresponding":[105],"can":[107],"obtain":[108],"more":[109],"accurate":[110],"at":[112],"least":[113],"equal":[114],"performance":[115],"determine":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
