{"id":"https://openalex.org/W2114846220","doi":"https://doi.org/10.1109/icpr.2008.4761359","title":"MCS-based balancing techniques for skewed classes: An empirical comparison","display_name":"MCS-based balancing techniques for skewed classes: An empirical comparison","publication_year":2008,"publication_date":"2008-12-01","ids":{"openalex":"https://openalex.org/W2114846220","doi":"https://doi.org/10.1109/icpr.2008.4761359","mag":"2114846220"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2008.4761359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2008.4761359","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 19th International Conference on Pattern Recognition","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/A5090932705","display_name":"Maria Teresa Ricamato","orcid":null},"institutions":[{"id":"https://openalex.org/I186995768","display_name":"Universit\u00e0 degli studi di Cassino e del Lazio Meridionale","ror":"https://ror.org/04nxkaq16","country_code":"IT","type":"education","lineage":["https://openalex.org/I186995768"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Maria Teresa Ricamato","raw_affiliation_strings":["DAEIMI Universit\u00e4t Hannover, Cassino, Italy","DAEIMI, Universitd degli Studi di Cassino, Cassino"],"affiliations":[{"raw_affiliation_string":"DAEIMI Universit\u00e4t Hannover, Cassino, Italy","institution_ids":[]},{"raw_affiliation_string":"DAEIMI, Universitd degli Studi di Cassino, Cassino","institution_ids":["https://openalex.org/I186995768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087449376","display_name":"Claudio Marrocco","orcid":"https://orcid.org/0000-0003-0840-7350"},"institutions":[{"id":"https://openalex.org/I186995768","display_name":"Universit\u00e0 degli studi di Cassino e del Lazio Meridionale","ror":"https://ror.org/04nxkaq16","country_code":"IT","type":"education","lineage":["https://openalex.org/I186995768"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Claudio Marrocco","raw_affiliation_strings":["DAEIMI Universit\u00e4t Hannover, Cassino, Italy","DAEIMI, Universitd degli Studi di Cassino, Cassino"],"affiliations":[{"raw_affiliation_string":"DAEIMI Universit\u00e4t Hannover, Cassino, Italy","institution_ids":[]},{"raw_affiliation_string":"DAEIMI, Universitd degli Studi di Cassino, Cassino","institution_ids":["https://openalex.org/I186995768"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050456869","display_name":"Francesco Tortorella","orcid":"https://orcid.org/0000-0002-5033-9323"},"institutions":[{"id":"https://openalex.org/I186995768","display_name":"Universit\u00e0 degli studi di Cassino e del Lazio Meridionale","ror":"https://ror.org/04nxkaq16","country_code":"IT","type":"education","lineage":["https://openalex.org/I186995768"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Tortorella","raw_affiliation_strings":["DAEIMI Universit\u00e4t Hannover, Cassino, Italy","DAEIMI, Universitd degli Studi di Cassino, Cassino"],"affiliations":[{"raw_affiliation_string":"DAEIMI Universit\u00e4t Hannover, Cassino, Italy","institution_ids":[]},{"raw_affiliation_string":"DAEIMI, Universitd degli Studi di Cassino, Cassino","institution_ids":["https://openalex.org/I186995768"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5090932705"],"corresponding_institution_ids":["https://openalex.org/I186995768"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.22354497,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"16","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9933000206947327,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9699000120162964,"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/oversampling","display_name":"Oversampling","score":0.9170935750007629},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7490274906158447},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6682593822479248},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6266747713088989},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5985516905784607},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5338213443756104},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5336495041847229},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49136796593666077},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.43110230565071106},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.14354458451271057}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.9170935750007629},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7490274906158447},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6682593822479248},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6266747713088989},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5985516905784607},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5338213443756104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5336495041847229},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49136796593666077},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.43110230565071106},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.14354458451271057},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2008.4761359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2008.4761359","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 19th International Conference on Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.214.5678","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.5678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://figment.cse.usf.edu/~sfefilat/data/papers/ThBT5.3.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1563938718","https://openalex.org/W1755925439","https://openalex.org/W2053724458","https://openalex.org/W2056614917","https://openalex.org/W2096451472","https://openalex.org/W2104167780","https://openalex.org/W2134546032","https://openalex.org/W2148143831","https://openalex.org/W2155653793","https://openalex.org/W2938524560","https://openalex.org/W3120740533","https://openalex.org/W3142980988","https://openalex.org/W6761450353"],"related_works":["https://openalex.org/W2766503024","https://openalex.org/W3196098778","https://openalex.org/W3211250490","https://openalex.org/W4360584310","https://openalex.org/W2953675148","https://openalex.org/W2981515171","https://openalex.org/W80466363","https://openalex.org/W2924282518","https://openalex.org/W3080872054","https://openalex.org/W2300921526"],"abstract_inverted_index":{"The":[0,76],"class":[1,67,74],"imbalance":[2],"is":[3,59,81],"a":[4,62,69,96],"critical":[5],"problem":[6],"in":[7,23,43,91],"classification":[8],"tasks":[9],"related":[10],"to":[11,82],"many":[12],"real":[13],"world":[14],"applications.":[15],"A":[16],"large":[17],"number":[18],"of":[19,40,52,71,78,86,112],"solutions":[20],"were":[21],"proposed":[22],"literature,":[24],"both":[25],"at":[26],"the":[27,37,50,65,72,84,101,106,113,116],"algorithmic":[28],"and":[29,68],"data":[30],"levels.":[31],"In":[32],"this":[33,79,92],"paper":[34],"we":[35,45],"analyze":[36],"second":[38],"kind":[39],"approach":[41,80],"and,":[42],"particular,":[44],"focus":[46],"our":[47],"attention":[48],"on":[49,61,115],"use":[51],"Multiple":[53],"Classification":[54],"Systems":[55],"where":[56],"each":[57],"classifier":[58],"trained":[60],"dataset":[63],"containing":[64],"minority":[66,102],"subset":[70],"majority":[73],"samples.":[75],"aim":[77],"avoid":[83],"drawbacks":[85],"other":[87],"methods,":[88],"commonly":[89],"used":[90],"context,":[93],"which":[94],"force":[95],"balanced":[97],"distribution":[98],"by":[99],"oversampling":[100],"class.":[103],"We":[104],"compare":[105],"results":[107],"obtained":[108],"applying":[109],"different":[110],"realizations":[111],"method":[114],"UCI":[117],"Repository":[118],"datasets.":[119]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
