{"id":"https://openalex.org/W2082417017","doi":"https://doi.org/10.1109/icnc.2012.6234723","title":"A new algorithm for imbalanced datasets in presence of outliers and noise","display_name":"A new algorithm for imbalanced datasets in presence of outliers and noise","publication_year":2012,"publication_date":"2012-05-01","ids":{"openalex":"https://openalex.org/W2082417017","doi":"https://doi.org/10.1109/icnc.2012.6234723","mag":"2082417017"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2012.6234723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2012.6234723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 8th International Conference on Natural Computation","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/A5039843189","display_name":"Shujuan Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shu-Juan Zhao","raw_affiliation_strings":["College of Science, Nanjing University of Posts and Telecommunications, Nanjing, China","College of Science, Nanjing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"College of Science, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"College of Science, Nanjing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025905335","display_name":"Huapeng Zhang","orcid":"https://orcid.org/0000-0002-1531-0103"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua-Peng Zhang","raw_affiliation_strings":["College of Science, Nanjing University of Posts and Telecommunications, Nanjing, China","College of Science, Nanjing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"College of Science, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"College of Science, Nanjing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100385652","display_name":"Lei Li","orcid":"https://orcid.org/0000-0001-7085-8262"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["College of Science, Nanjing University of Posts and Telecommunications, Nanjing, China","College of Science, Nanjing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"College of Science, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"College of Science, Nanjing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5039843189"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.8563,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.79418178,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"30","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9994999766349792,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9994999766349792,"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":0.9848999977111816,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.98089998960495,"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/outlier","display_name":"Outlier","score":0.8495714664459229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7051489353179932},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6803644895553589},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6799010038375854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6595484018325806},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6483209133148193},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5789987444877625},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.563611626625061},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5401775240898132},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5291127562522888},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41916701197624207},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4158133864402771},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3760138750076294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24397176504135132},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06346529722213745}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8495714664459229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7051489353179932},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6803644895553589},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6799010038375854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6595484018325806},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6483209133148193},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5789987444877625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.563611626625061},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5401775240898132},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5291127562522888},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41916701197624207},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4158133864402771},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3760138750076294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24397176504135132},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06346529722213745},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc.2012.6234723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2012.6234723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 8th International Conference on Natural Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W85350352","https://openalex.org/W1502069036","https://openalex.org/W1994807229","https://openalex.org/W2108697353","https://openalex.org/W2109283550","https://openalex.org/W2118978333","https://openalex.org/W2119821739","https://openalex.org/W2138079527","https://openalex.org/W2147813562","https://openalex.org/W2149684865","https://openalex.org/W2912565176","https://openalex.org/W2979832949","https://openalex.org/W4211007335","https://openalex.org/W4234819098","https://openalex.org/W4237065586","https://openalex.org/W4239510810","https://openalex.org/W6603460400","https://openalex.org/W6675953175"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2090763504","https://openalex.org/W2357409937","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W2580722822","https://openalex.org/W148178222","https://openalex.org/W2772305933"],"abstract_inverted_index":{"In":[0,65],"recent":[1],"years,":[2],"learning":[3],"from":[4],"imbalanced":[5,46,85],"datasets":[6,86,98],"has":[7],"attracted":[8],"much":[9],"attention":[10],"both":[11],"in":[12,44,61,87,105],"academic":[13],"and":[14,42,59,91],"industrial":[15],"fields.":[16],"The":[17],"kernel":[18,74],"modification":[19,75],"method":[20,28,76,101],"based":[21,77],"on":[22,78,95],"Riemannian":[23,79],"metric":[24,80],"is":[25],"an":[26],"effective":[27,104],"to":[29,82,102],"handle":[30,83],"the":[31,40,45,57,62,70,73,84],"class":[32,107],"imbalance":[33],"problem.":[34],"But":[35],"it":[36],"cannot":[37],"deal":[38,55],"with":[39,56,72],"outliers":[41,58,90],"noise":[43,60],"datasets.":[47,64],"However,":[48],"Fuzzy":[49],"Support":[50],"Vector":[51],"Machine":[52],"(FSVM)":[53],"can":[54],"balanced":[63],"this":[66,100],"paper,":[67],"we":[68],"combine":[69],"FSVM":[71],"together":[81],"presence":[88],"of":[89],"noise.":[92],"Experimental":[93],"results":[94],"four":[96],"UCI":[97],"show":[99],"be":[103],"improving":[106],"prediction":[108],"accuracy.":[109]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}