{"id":"https://openalex.org/W2113203372","doi":"https://doi.org/10.1109/ijcnn.2003.1223408","title":"How many neighbors to consider in pattern pre-selection for support vector classifiers?","display_name":"How many neighbors to consider in pattern pre-selection for support vector classifiers?","publication_year":2004,"publication_date":"2004-03-01","ids":{"openalex":"https://openalex.org/W2113203372","doi":"https://doi.org/10.1109/ijcnn.2003.1223408","mag":"2113203372"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2003.1223408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","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/A5043830800","display_name":"Hyunjung Shin","orcid":"https://orcid.org/0000-0001-8347-8277"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyunjung Shin","raw_affiliation_strings":["Department of Industrial Engineering, Seoul national University, Seoul, South Korea","Dept. of Ind. Eng., Seoul Nat. Univ., South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Seoul national University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Dept. of Ind. Eng., Seoul Nat. Univ., South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102814007","display_name":"Sungzoon Cho","orcid":"https://orcid.org/0000-0002-1695-1973"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungzoon Cho","raw_affiliation_strings":["Department of Industrial Engineering, Seoul national University, Seoul, South Korea","Dept. of Ind. Eng., Seoul Nat. Univ., South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Seoul national University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Dept. of Ind. Eng., Seoul Nat. Univ., South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5043830800"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":1.1035,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79831964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"565","last_page":"570"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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":0.9990000128746033,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9986000061035156,"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/T10320","display_name":"Neural Networks and Applications","score":0.9975000023841858,"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/decision-boundary","display_name":"Decision boundary","score":0.8146156072616577},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7152822017669678},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6950699090957642},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6086719632148743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5964255332946777},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5940794348716736},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5918527245521545},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43167683482170105},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37293756008148193}],"concepts":[{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.8146156072616577},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7152822017669678},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6950699090957642},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6086719632148743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5964255332946777},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5940794348716736},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5918527245521545},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43167683482170105},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37293756008148193},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2003.1223408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.mpg.de:item_1792399","is_oa":false,"landing_page_url":"http://hdl.handle.net/11858/00-001M-0000-0013-DC1E-2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6399999856948853,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1512098439","https://openalex.org/W1529939802","https://openalex.org/W1541717805","https://openalex.org/W1879377151","https://openalex.org/W2008056655","https://openalex.org/W2113853244","https://openalex.org/W2127406992","https://openalex.org/W2132407367","https://openalex.org/W2137532058","https://openalex.org/W2366113695","https://openalex.org/W4244864805","https://openalex.org/W6630527977","https://openalex.org/W6826462234"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W1948992892","https://openalex.org/W2104657898","https://openalex.org/W1886884218","https://openalex.org/W184442817","https://openalex.org/W2009611918","https://openalex.org/W2814966788","https://openalex.org/W1983643426","https://openalex.org/W2130203723"],"abstract_inverted_index":{"Training":[0],"support":[1],"vector":[2],"classifiers":[3],"(SVC)":[4],"requires":[5],"large":[6],"memory":[7],"and":[8,96],"long":[9],"cpu":[10],"time":[11],"when":[12],"the":[13,20,35,38,42,62,66],"pattern":[14,57],"set":[15],"is":[16,74],"large.":[17],"To":[18],"alleviate":[19],"computational":[21],"burden":[22],"in":[23,37,87],"SVC":[24],"training,":[25],"we":[26],"previously":[27],"proposed":[28],"a":[29,81,90],"preprocessing":[30],"algorithm":[31],"which":[32],"selects":[33],"only":[34],"patterns":[36],"overlap":[39],"region":[40],"around":[41],"decision":[43,67],"boundary,":[44],"based":[45],"on":[46],"neighborhood":[47],"properties.":[48],"The":[49,69],"k-nearest":[50],"neighbors'":[51],"class":[52],"label":[53],"entropy":[54],"for":[55],"each":[56],"was":[58],"used":[59],"to":[60,65,93],"estimate":[61],"pattern's":[63],"proximity":[64],"boundary.":[68],"value":[70],"of":[71],"parameter":[72],"k":[73,95],"critical,":[75],"yet":[76],"has":[77],"been":[78],"determined":[79],"by":[80],"rather":[82],"ad-hoc":[83],"fashion.":[84],"We":[85],"propose":[86],"this":[88],"paper":[89],"systematic":[91],"procedure":[92],"determine":[94],"show":[97],"its":[98],"effectiveness":[99],"through":[100],"experiments.":[101]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}