{"id":"https://openalex.org/W2991198822","doi":"https://doi.org/10.1016/j.ins.2019.10.017","title":"Kernel density estimation based sampling for imbalanced class distribution","display_name":"Kernel density estimation based sampling for imbalanced class distribution","publication_year":2019,"publication_date":"2019-10-16","ids":{"openalex":"https://openalex.org/W2991198822","doi":"https://doi.org/10.1016/j.ins.2019.10.017","mag":"2991198822"},"language":"en","primary_location":{"id":"doi:10.1016/j.ins.2019.10.017","doi":"https://doi.org/10.1016/j.ins.2019.10.017","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.ins.2019.10.017","pdf_url":null,"source":{"id":"https://openalex.org/S192650101","display_name":"Information Sciences","issn_l":"0020-0255","issn":["0020-0255","1872-6291"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-b","fnege-4","jufo-3","ki-jl-1","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information Sciences","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.07842","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051609871","display_name":"Firuz Kamalov","orcid":"https://orcid.org/0000-0003-3946-0920","observed_orcids":["https://orcid.org/0000-0003-3946-0920"]},"institutions":[{"id":"https://openalex.org/I186129607","display_name":"Canadian University of Dubai","ror":"https://ror.org/029zgsn59","country_code":"AE","type":"education","lineage":["https://openalex.org/I186129607"]}],"countries":["AE"],"is_corresponding":true,"raw_author_name":"Firuz Kamalov","raw_affiliation_strings":["Department of Electrical Engineering, Canadian University Dubai, Dubai, United Arab Emirates"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Canadian University Dubai, Dubai, United Arab Emirates","institution_ids":["https://openalex.org/I186129607"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5051609871"],"corresponding_institution_ids":["https://openalex.org/I186129607"],"apc_list":{"value":3300,"currency":"USD","value_usd":3300},"apc_paid":null,"fwci":5.9207,"has_fulltext":false,"cited_by_count":153,"citation_normalized_percentile":{"value":0.96928573,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"512","issue":null,"first_page":"1192","last_page":"1201"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":1.0,"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":1.0,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.0,"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/T12384","display_name":"Customer churn and segmentation","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.8240000009536743},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"kernel density estimation","score":0.9290000200271606},{"id":"https://openalex.org/keywords/oversampling","display_name":"oversampling","score":0.7770000100135803},{"id":"https://openalex.org/keywords/synthetic-minority-samples","display_name":"synthetic minority samples","score":0.47099998593330383},{"id":"https://openalex.org/keywords/overfitting","display_name":"overfitting","score":0.8610000014305115},{"id":"https://openalex.org/keywords/classification","display_name":"classification","score":0.31299999356269836},{"id":"https://openalex.org/keywords/fraud-detection","display_name":"fraud detection","score":0.6890000104904175},{"id":"https://openalex.org/keywords/intrusion-detection","display_name":"intrusion detection","score":0.9020000100135803}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7303217649459839},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.6851054430007935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6471684575080872},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.5774511694908142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5546780228614807},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5197084546089172},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.50180983543396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4790588319301605},{"id":"https://openalex.org/C167723999","wikidata":"https://www.wikidata.org/wiki/Q3773214","display_name":"Sampling distribution","level":2,"score":0.47296422719955444},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4661603569984436},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.46101465821266174},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.454015851020813},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4518061876296997},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.42797237634658813},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40938982367515564},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39388149976730347},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3060877323150635},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08744579553604126},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1016/j.ins.2019.10.017","doi":"https://doi.org/10.1016/j.ins.2019.10.017","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.ins.2019.10.017","pdf_url":null,"source":{"id":"https://openalex.org/S192650101","display_name":"Information Sciences","issn_l":"0020-0255","issn":["0020-0255","1872-6291"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-b","fnege-4","jufo-3","ki-jl-1","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information Sciences","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1910.07842","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.07842","pdf_url":"https://arxiv.org/pdf/1910.07842","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1910.07842","doi":"https://doi.org/10.48550/arxiv.1910.07842","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.07842","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.07842","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.07842","pdf_url":"https://arxiv.org/pdf/1910.07842","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4000000059604645}],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions","score":0.699999988079071}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W580216800","https://openalex.org/W619160221","https://openalex.org/W1495177430","https://openalex.org/W1753659477","https://openalex.org/W1864224110","https://openalex.org/W1975664724","https://openalex.org/W2002830978","https://openalex.org/W2017468850","https://openalex.org/W2023299139","https://openalex.org/W2103041471","https://openalex.org/W2104167780","https://openalex.org/W2104933073","https://openalex.org/W2118978333","https://openalex.org/W2129905273","https://openalex.org/W2148143831","https://openalex.org/W2150559772","https://openalex.org/W2153464267","https://openalex.org/W2158698691","https://openalex.org/W2159245256","https://openalex.org/W2168508521","https://openalex.org/W2169522260","https://openalex.org/W2170955556","https://openalex.org/W2173314530","https://openalex.org/W2185967890","https://openalex.org/W2279597087","https://openalex.org/W2338318698","https://openalex.org/W2521200999","https://openalex.org/W2540352327","https://openalex.org/W2547788783","https://openalex.org/W2562319768","https://openalex.org/W2567669303","https://openalex.org/W2612634114","https://openalex.org/W2763619424","https://openalex.org/W2797602122","https://openalex.org/W2800788706","https://openalex.org/W2950495522","https://openalex.org/W3005347330","https://openalex.org/W3010653466","https://openalex.org/W3104298728","https://openalex.org/W3155649056","https://openalex.org/W4205930639","https://openalex.org/W4247993926","https://openalex.org/W4296472359","https://openalex.org/W4300048831","https://openalex.org/W6684560594","https://openalex.org/W6685016812"],"related_works":["https://openalex.org/W2099378941","https://openalex.org/W109499086","https://openalex.org/W4234130083","https://openalex.org/W2591955297","https://openalex.org/W2159078175","https://openalex.org/W2019800484","https://openalex.org/W1859106888","https://openalex.org/W4401449196","https://openalex.org/W2390718074","https://openalex.org/W4309301054"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":22},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":12}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-12-05T00:00:00"}
