{"id":"https://openalex.org/W2794133560","doi":"https://doi.org/10.1504/ijict.2018.10011701","title":"Boosting prediction performance on imbalanced dataset","display_name":"Boosting prediction performance on imbalanced dataset","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2794133560","doi":"https://doi.org/10.1504/ijict.2018.10011701","mag":"2794133560"},"language":"en","primary_location":{"id":"doi:10.1504/ijict.2018.10011701","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijict.2018.10011701","pdf_url":null,"source":{"id":"https://openalex.org/S168803321","display_name":"International Journal of Information and Communication Technology","issn_l":"1466-6642","issn":["1466-6642","1741-8070"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information and Communication Technology","raw_type":"journal-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/A5009550171","display_name":"Masoumeh Zareapoor","orcid":"https://orcid.org/0000-0002-3991-0584"},"institutions":[{"id":"https://openalex.org/I19716509","display_name":"Jamia Hamdard","ror":"https://ror.org/03dwxvb85","country_code":"IN","type":"education","lineage":["https://openalex.org/I19716509"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Masoumeh Zareapoor","raw_affiliation_strings":["Department of Computer Science, Jamia Hamdard University, New Delhi, 110062, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Jamia Hamdard University, New Delhi, 110062, India","institution_ids":["https://openalex.org/I19716509"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079232252","display_name":"Pourya Shamsolmoali","orcid":"https://orcid.org/0000-0002-0263-1661"},"institutions":[{"id":"https://openalex.org/I19716509","display_name":"Jamia Hamdard","ror":"https://ror.org/03dwxvb85","country_code":"IN","type":"education","lineage":["https://openalex.org/I19716509"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pourya Shamsolmoali","raw_affiliation_strings":["Department of Computer Science, Jamia Hamdard University, New Delhi, 110062, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Jamia Hamdard University, New Delhi, 110062, India","institution_ids":["https://openalex.org/I19716509"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19716509"],"apc_list":null,"apc_paid":null,"fwci":0.338,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67169584,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"13","issue":"2","first_page":"186","last_page":"186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","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"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","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"}},{"id":"https://openalex.org/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9677000045776367,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9459999799728394,"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":0.8799047470092773},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7831321954727173},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5876849889755249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.578241229057312},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40641582012176514}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8799047470092773},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7831321954727173},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5876849889755249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.578241229057312},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40641582012176514}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijict.2018.10011701","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijict.2018.10011701","pdf_url":null,"source":{"id":"https://openalex.org/S168803321","display_name":"International Journal of Information and Communication Technology","issn_l":"1466-6642","issn":["1466-6642","1741-8070"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information and Communication Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4286629047","https://openalex.org/W3082059448","https://openalex.org/W4313640622","https://openalex.org/W3046775127","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3107602296"],"abstract_inverted_index":{"Mining":[0],"from":[1],"imbalance":[2,82],"data":[3,83,94,115],"is":[4,16,21,29,56,71,95,125],"an":[5,140,145],"important":[6,59],"problem":[7],"in":[8,78],"algorithmic":[9],"and":[10],"performance":[11,65,91,121,162],"evaluation.":[12],"When":[13],"a":[14,75,88],"dataset":[15],"imbalanced,":[17],"the":[18,26,32,49,52,57,64,79,93,114,117,120,123,130,135,151,159],"classification":[19],"technique":[20,143],"not":[22,36,86],"equal":[23],"considering":[24],"both":[25],"classes.":[27],"It":[28],"obvious":[30],"that":[31],"standard":[33],"classifiers":[34,124],"are":[35],"suitable":[37],"to":[38,73,102,108,116,149],"deal":[39],"with":[40,144],"imbalanced":[41,132,166],"data,":[42],"since":[43],"they":[44],"will":[45],"likely":[46],"classify":[47],"all":[48],"instances":[50],"into":[51],"majority":[53],"class,":[54],"which":[55,70],"less":[58],"class.":[60],"Additionally":[61],"some":[62],"of":[63,81,122,129,134,147],"measurement,":[66],"like":[67],"accuracy":[68],"-":[69,84],"known":[72],"be":[74],"biased":[76],"metric":[77],"case":[80],"does":[85],"have":[87],"very":[89],"good":[90],"when":[92],"imbalanced.":[96],"In":[97],"this":[98],"paper,":[99],"we":[100,138,157],"tried":[101],"apply":[103],"various":[104],"techniques":[105],"used":[106],"commonly":[107],"handle":[109],"class":[110],"imbalance,":[111],"before":[112],"giving":[113],"classifiers.":[118],"But,":[119],"found":[126],"degrading":[127],"because":[128],"highly":[131],"nature":[133],"datasets.":[136,167],"Hence,":[137],"propose":[139],"integrated":[141],"sampling":[142],"ensemble":[146],"AdaBoost":[148],"improve":[150],"prediction":[152],"performance.":[153],"Meanwhile,":[154],"through":[155],"empirical,":[156],"show":[158],"more":[160],"appropriate":[161],"measures":[163],"for":[164],"mining":[165]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
