{"id":"https://openalex.org/W2916913565","doi":"https://doi.org/10.1109/access.2019.2899578","title":"Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data","display_name":"Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2916913565","doi":"https://doi.org/10.1109/access.2019.2899578","mag":"2916913565"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2899578","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2899578","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08651567.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08651567.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042281125","display_name":"Solomon H. Ebenuwa","orcid":"https://orcid.org/0000-0001-5780-4817"},"institutions":[{"id":"https://openalex.org/I157227730","display_name":"University of East London","ror":"https://ror.org/057jrqr44","country_code":"GB","type":"education","lineage":["https://openalex.org/I157227730"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Solomon H. Ebenuwa","raw_affiliation_strings":["School of Architecture Computing and Engineering, University of East London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5780-4817","affiliations":[{"raw_affiliation_string":"School of Architecture Computing and Engineering, University of East London, London, U.K","institution_ids":["https://openalex.org/I157227730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070246091","display_name":"Mhd Saeed Sharif","orcid":"https://orcid.org/0000-0002-4008-8049"},"institutions":[{"id":"https://openalex.org/I157227730","display_name":"University of East London","ror":"https://ror.org/057jrqr44","country_code":"GB","type":"education","lineage":["https://openalex.org/I157227730"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mhd Saeed Sharif","raw_affiliation_strings":["School of Architecture Computing and Engineering, University of East London, London, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Architecture Computing and Engineering, University of East London, London, U.K","institution_ids":["https://openalex.org/I157227730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018409592","display_name":"Mamoun Alazab","orcid":"https://orcid.org/0000-0002-1928-3704"},"institutions":[{"id":"https://openalex.org/I29894533","display_name":"Charles Darwin University","ror":"https://ror.org/048zcaj52","country_code":"AU","type":"education","lineage":["https://openalex.org/I29894533"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mamoun Alazab","raw_affiliation_strings":["College of Engineering, IT & Environment, Charles Darwin University, Casuarina, NT, Australia"],"raw_orcid":"https://orcid.org/0000-0002-1928-3704","affiliations":[{"raw_affiliation_string":"College of Engineering, IT & Environment, Charles Darwin University, Casuarina, NT, Australia","institution_ids":["https://openalex.org/I29894533"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108774092","display_name":"Ameer Al-Nemrat","orcid":null},"institutions":[{"id":"https://openalex.org/I157227730","display_name":"University of East London","ror":"https://ror.org/057jrqr44","country_code":"GB","type":"education","lineage":["https://openalex.org/I157227730"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ameer Al-Nemrat","raw_affiliation_strings":["School of Architecture Computing and Engineering, University of East London, London, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Architecture Computing and Engineering, University of East London, London, U.K","institution_ids":["https://openalex.org/I157227730"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5042281125"],"corresponding_institution_ids":["https://openalex.org/I157227730"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":11.4691,"has_fulltext":true,"cited_by_count":114,"citation_normalized_percentile":{"value":0.98708822,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"24649","last_page":"24666"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9700999855995178,"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/computer-science","display_name":"Computer science","score":0.7141115665435791},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6969661712646484},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6739634871482849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6431754231452942},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6366913318634033},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5166847705841064},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5119298696517944},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5049915909767151},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4980285167694092},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4534688889980316},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.44430670142173767}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7141115665435791},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6969661712646484},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6739634871482849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6431754231452942},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6366913318634033},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5166847705841064},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5119298696517944},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5049915909767151},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4980285167694092},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4534688889980316},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.44430670142173767},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/access.2019.2899578","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2899578","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08651567.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:roar.uel.ac.uk:8087","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400937","display_name":"ROAR (University of East London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I157227730","host_organization_name":"University of East London","host_organization_lineage":["https://openalex.org/I157227730"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:2669390714604dc0a47e0e9234b8131b","is_oa":true,"landing_page_url":"https://doaj.org/article/2669390714604dc0a47e0e9234b8131b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 24649-24666 (2019)","raw_type":"article"},{"id":"pmh:oai:repository.uel.ac.uk:8449v","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ACCESS.2019.2899578","pdf_url":null,"source":{"id":"https://openalex.org/S4306401301","display_name":"UEL Research Repository (University of East London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I157227730","host_organization_name":"University of East London","host_organization_lineage":["https://openalex.org/I157227730"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2899578","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2899578","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08651567.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2916913565.pdf","grobid_xml":"https://content.openalex.org/works/W2916913565.grobid-xml"},"referenced_works_count":99,"referenced_works":["https://openalex.org/W405632","https://openalex.org/W57841519","https://openalex.org/W69407335","https://openalex.org/W87312633","https://openalex.org/W167016754","https://openalex.org/W195533127","https://openalex.org/W218853445","https://openalex.org/W752888290","https://openalex.org/W958993015","https://openalex.org/W1501500081","https://openalex.org/W1560107318","https://openalex.org/W1574534563","https://openalex.org/W1575476631","https://openalex.org/W1623006543","https://openalex.org/W1933098239","https://openalex.org/W1961147827","https://openalex.org/W2012035409","https://openalex.org/W2012105789","https://openalex.org/W2014620499","https://openalex.org/W2015452969","https://openalex.org/W2023639956","https://openalex.org/W2032699694","https://openalex.org/W2036187215","https://openalex.org/W2041282815","https://openalex.org/W2051695802","https://openalex.org/W2052611008","https://openalex.org/W2069321575","https://openalex.org/W2071808384","https://openalex.org/W2086184041","https://openalex.org/W2088220893","https://openalex.org/W2088950943","https://openalex.org/W2095398418","https://openalex.org/W2102705643","https://openalex.org/W2103614420","https://openalex.org/W2103685142","https://openalex.org/W2104167780","https://openalex.org/W2106253349","https://openalex.org/W2109574129","https://openalex.org/W2109676405","https://openalex.org/W2124316651","https://openalex.org/W2125876917","https://openalex.org/W2130745297","https://openalex.org/W2130898128","https://openalex.org/W2133506114","https://openalex.org/W2136903812","https://openalex.org/W2140190241","https://openalex.org/W2141083048","https://openalex.org/W2146619110","https://openalex.org/W2148143831","https://openalex.org/W2149284637","https://openalex.org/W2149381612","https://openalex.org/W2153803020","https://openalex.org/W2156773695","https://openalex.org/W2158698691","https://openalex.org/W2159699146","https://openalex.org/W2164330572","https://openalex.org/W2165837041","https://openalex.org/W2170505850","https://openalex.org/W2181866432","https://openalex.org/W2190423096","https://openalex.org/W2262581580","https://openalex.org/W2386865585","https://openalex.org/W2466023328","https://openalex.org/W2468645505","https://openalex.org/W2488193130","https://openalex.org/W2498119267","https://openalex.org/W2516328000","https://openalex.org/W2536062280","https://openalex.org/W2540844077","https://openalex.org/W2549437329","https://openalex.org/W2569168369","https://openalex.org/W2587314106","https://openalex.org/W2756182389","https://openalex.org/W2781233062","https://openalex.org/W2791165267","https://openalex.org/W2883429111","https://openalex.org/W2938423815","https://openalex.org/W2962795289","https://openalex.org/W2998216295","https://openalex.org/W4210764542","https://openalex.org/W4240616498","https://openalex.org/W4247128285","https://openalex.org/W4285719527","https://openalex.org/W6600017900","https://openalex.org/W6602343995","https://openalex.org/W6602766936","https://openalex.org/W6603553207","https://openalex.org/W6606837198","https://openalex.org/W6607976765","https://openalex.org/W6608790104","https://openalex.org/W6633497745","https://openalex.org/W6634321592","https://openalex.org/W6636749155","https://openalex.org/W6641082943","https://openalex.org/W6678631417","https://openalex.org/W6680202767","https://openalex.org/W6687537609","https://openalex.org/W6719473894","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W2188500270","https://openalex.org/W2303858293","https://openalex.org/W2915512527","https://openalex.org/W51364034","https://openalex.org/W2793336762","https://openalex.org/W2091548507","https://openalex.org/W2368816706","https://openalex.org/W3159414774","https://openalex.org/W4385728102","https://openalex.org/W2378093739"],"abstract_inverted_index":{"Data":[0],"are":[1,136],"being":[2],"generated":[3],"and":[4,43,128,131,175,202,219,226,246],"used":[5],"to":[6,16,31,61,166,190,198],"support":[7,216],"all":[8],"aspects":[9],"of":[10,19,27,36,50,75,114,244],"healthcare":[11],"provision,":[12],"from":[13,29],"policy":[14],"formation":[15],"the":[17,25,34,48,59,76,96,101,107,115,172,192,199,235,248],"delivery":[18],"primary":[20],"care":[21],"services.":[22],"Particularly,":[23],"with":[24],"change":[26],"emphasis":[28],"curative":[30],"preventive":[32],"medicine,":[33],"importance":[35],"data-based":[37],"research":[38],"such":[39],"as":[40,139],"data":[41],"mining":[42],"machine":[44,78],"learning":[45,79],"has":[46,119],"emphasized":[47],"issues":[49],"class":[51,65,86,104,118,156],"distributions":[52],"in":[53,67,87,91,94,109,121,124,158],"datasets.":[54],"In":[55],"typical":[56],"predictive":[57],"modeling,":[58],"inability":[60],"effectively":[62],"address":[63],"a":[64,68,84,145,159,182],"imbalance":[66,155],"real-life":[69],"dataset":[70],"is":[71,105],"an":[72,241],"important":[73],"shortcoming":[74],"existing":[77],"algorithms.":[80],"Most":[81],"algorithms":[82],"assume":[83],"balanced":[85],"their":[88],"design,":[89],"resulting":[90],"poor":[92],"performance":[93],"predicting":[95,110],"minority":[97,102,116],"target":[98,103,117],"class.":[99],"Ironically,":[100],"usually":[106],"focus":[108],"processes.":[111],"The":[112,161,222,237],"misclassification":[113],"resulted":[120],"serious":[122],"consequences":[123],"detecting":[125,129],"chronic":[126],"diseases":[127],"fraud":[130],"intrusion":[132],"where":[133,250],"positive":[134],"cases":[135],"erroneously":[137],"predicted":[138],"not":[140,258],"positive.":[141],"This":[142,179],"paper":[143,180],"presents":[144],"new":[146],"attribute":[147,169,195],"selection":[148,170,196],"technique":[149,186,239],"called":[150],"variance":[151,193,224],"ranking":[152,194,225],"for":[153],"handling":[154],"problems":[157],"dataset.":[160],"results":[162,233],"obtained":[163],"were":[164,255],"compared":[165,197],"two":[167],"well-known":[168],"techniques:":[171],"Pearson":[173,200],"correlation":[174],"information":[176,203],"gain":[177],"technique.":[178],"uses":[181],"novel":[183],"similarity":[184,229,252],"measurement":[185,253],"ranked":[187,227],"order":[188,228],"similarity-ROS":[189],"evaluate":[191],"correlations":[201],"gain.":[204],"Further":[205],"validation":[206],"was":[207],"carried":[208],"out":[209],"using":[210],"three":[211],"binary":[212],"classifications:":[213],"logistic":[214],"regression,":[215],"vector":[217],"machine,":[218],"decision":[220],"tree.":[221],"proposed":[223],"techniques":[230,254],"showed":[231],"better":[232],"than":[234],"benchmarks.":[236],"ROS":[238],"provided":[240],"excellent":[242],"means":[243],"grading":[245],"measuring":[247],"similarities":[249],"other":[251],"inadequate":[256],"or":[257],"applicable.":[259]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":10}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}