{"id":"https://openalex.org/W4214726431","doi":"https://doi.org/10.3390/s22041373","title":"Comparing Sampling Strategies for Tackling Imbalanced Data in Human Activity Recognition","display_name":"Comparing Sampling Strategies for Tackling Imbalanced Data in Human Activity Recognition","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4214726431","doi":"https://doi.org/10.3390/s22041373","pmid":"https://pubmed.ncbi.nlm.nih.gov/35214275"},"language":"en","primary_location":{"id":"doi:10.3390/s22041373","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22041373","pdf_url":"https://www.mdpi.com/1424-8220/22/4/1373/pdf?version=1644560773","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/4/1373/pdf?version=1644560773","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041915757","display_name":"Fayez Alharbi","orcid":"https://orcid.org/0009-0006-5837-236X"},"institutions":[{"id":"https://openalex.org/I195631090","display_name":"Majmaah University","ror":"https://ror.org/01mcrnj60","country_code":"SA","type":"education","lineage":["https://openalex.org/I195631090"]},{"id":"https://openalex.org/I55521800","display_name":"Goldsmiths University of London","ror":"https://ror.org/01khx4a30","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I55521800"]}],"countries":["GB","SA"],"is_corresponding":true,"raw_author_name":"Fayez Alharbi","raw_affiliation_strings":["Computer Sciences and Information Technology College, Majmaah University, Al Majmaah 15341, Saudi Arabia","Department of Computing, Goldsmiths, University of London, London SE14 6NW, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Sciences and Information Technology College, Majmaah University, Al Majmaah 15341, Saudi Arabia","institution_ids":["https://openalex.org/I195631090"]},{"raw_affiliation_string":"Department of Computing, Goldsmiths, University of London, London SE14 6NW, UK","institution_ids":["https://openalex.org/I55521800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041863006","display_name":"Lahcen Ouarbya","orcid":null},"institutions":[{"id":"https://openalex.org/I55521800","display_name":"Goldsmiths University of London","ror":"https://ror.org/01khx4a30","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I55521800"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lahcen Ouarbya","raw_affiliation_strings":["Department of Computing, Goldsmiths, University of London, London SE14 6NW, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computing, Goldsmiths, University of London, London SE14 6NW, UK","institution_ids":["https://openalex.org/I55521800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089445707","display_name":"Jamie A. Ward","orcid":"https://orcid.org/0000-0002-9637-6066"},"institutions":[{"id":"https://openalex.org/I55521800","display_name":"Goldsmiths University of London","ror":"https://ror.org/01khx4a30","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I55521800"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jamie A Ward","raw_affiliation_strings":["Department of Computing, Goldsmiths, University of London, London SE14 6NW, UK"],"raw_orcid":"https://orcid.org/0000-0002-9637-6066","affiliations":[{"raw_affiliation_string":"Department of Computing, Goldsmiths, University of London, London SE14 6NW, UK","institution_ids":["https://openalex.org/I55521800"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041915757"],"corresponding_institution_ids":["https://openalex.org/I195631090","https://openalex.org/I55521800"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":3.4841,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.93266321,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"22","issue":"4","first_page":"1373","last_page":"1373"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9944999814033508,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9944999814033508,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.993399977684021,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9803000092506409,"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":0.91346675157547},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7120450735092163},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6837198138237},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6354318857192993},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6308095455169678},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.5855655074119568},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.4425809681415558},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4201815724372864},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.41100168228149414}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.91346675157547},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7120450735092163},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6837198138237},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6354318857192993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6308095455169678},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.5855655074119568},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.4425809681415558},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4201815724372864},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.41100168228149414},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":7,"locations":[{"id":"doi:10.3390/s22041373","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22041373","pdf_url":"https://www.mdpi.com/1424-8220/22/4/1373/pdf?version=1644560773","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:35214275","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35214275","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:eprints.gold.ac.uk:31457","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400496","display_name":"Goldsmiths (University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Published Version","raw_type":"Article"},{"id":"pmh:oai:eprints.gold.ac.uk:31457","is_oa":false,"landing_page_url":"https://orcid.org/0000-0002-9637-6066>.","pdf_url":null,"source":{"id":"https://openalex.org/S4306400496","display_name":"Goldsmiths (University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Published Version","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:74e01fc00b544c23a5326aef5b81554a","is_oa":true,"landing_page_url":"https://doaj.org/article/74e01fc00b544c23a5326aef5b81554a","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":"Sensors, Vol 22, Iss 4, p 1373 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/4/1373/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22041373","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 4; Pages: 1373","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8963022","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8963022","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22041373","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22041373","pdf_url":"https://www.mdpi.com/1424-8220/22/4/1373/pdf?version=1644560773","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320319993","display_name":"Leverhulme Trust","ror":"https://ror.org/012mzw131"},{"id":"https://openalex.org/F4320320004","display_name":"British Academy","ror":"https://ror.org/0302b4677"},{"id":"https://openalex.org/F4320320005","display_name":"Royal Academy of Engineering","ror":"https://ror.org/0526snb40"},{"id":"https://openalex.org/F4320324553","display_name":"Majmaah University","ror":"https://ror.org/01mcrnj60"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4214726431.pdf","grobid_xml":"https://content.openalex.org/works/W4214726431.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W85350352","https://openalex.org/W123443654","https://openalex.org/W175634338","https://openalex.org/W571200655","https://openalex.org/W1527911497","https://openalex.org/W1534477342","https://openalex.org/W1565746575","https://openalex.org/W1854498722","https://openalex.org/W1984757884","https://openalex.org/W1993220166","https://openalex.org/W2023302299","https://openalex.org/W2034841618","https://openalex.org/W2054780155","https://openalex.org/W2063598276","https://openalex.org/W2073401630","https://openalex.org/W2101234009","https://openalex.org/W2105046342","https://openalex.org/W2107138773","https://openalex.org/W2118978333","https://openalex.org/W2120336810","https://openalex.org/W2126511896","https://openalex.org/W2132603770","https://openalex.org/W2134524950","https://openalex.org/W2136744557","https://openalex.org/W2139986471","https://openalex.org/W2148143831","https://openalex.org/W2166712377","https://openalex.org/W2167460663","https://openalex.org/W2170505850","https://openalex.org/W2270470215","https://openalex.org/W2288074780","https://openalex.org/W2304267454","https://openalex.org/W2342667915","https://openalex.org/W2500814170","https://openalex.org/W2544836728","https://openalex.org/W2562319768","https://openalex.org/W2594116048","https://openalex.org/W2734442025","https://openalex.org/W2794717185","https://openalex.org/W2795342689","https://openalex.org/W2803294438","https://openalex.org/W2890264806","https://openalex.org/W2897551993","https://openalex.org/W2927635891","https://openalex.org/W2963563124","https://openalex.org/W2969674096","https://openalex.org/W2972393330","https://openalex.org/W3001316388","https://openalex.org/W3015351929","https://openalex.org/W3083323811","https://openalex.org/W3084255915","https://openalex.org/W3104239639","https://openalex.org/W3106983564","https://openalex.org/W6605080955","https://openalex.org/W6675354045","https://openalex.org/W6704209889","https://openalex.org/W6749875753","https://openalex.org/W6767110884","https://openalex.org/W6772938244"],"related_works":["https://openalex.org/W2766503024","https://openalex.org/W4401045170","https://openalex.org/W3172259201","https://openalex.org/W2903618681","https://openalex.org/W3184937791","https://openalex.org/W4401052546","https://openalex.org/W2811014843","https://openalex.org/W2117913171","https://openalex.org/W3105278570","https://openalex.org/W2582769230"],"abstract_inverted_index":{"Human":[0],"activity":[1],"recognition":[2],"(HAR)":[3],"using":[4,69,231],"wearable":[5],"sensors":[6],"is":[7,38,73],"an":[8],"increasingly":[9],"active":[10],"research":[11],"topic":[12],"in":[13,17,46,50],"machine":[14],"learning,":[15],"aided":[16],"part":[18],"by":[19,257],"the":[20,62,109,137,147,165,175,186,199,217,220,225,248,275],"ready":[21],"availability":[22],"of":[23,36,61,102,111,119,160,219,250,260],"detailed":[24],"motion":[25],"capture":[26,116],"data":[27,76,233],"from":[28,105,234],"smartphones,":[29],"fitness":[30],"trackers,":[31],"and":[32,58,80,185,208,229,245,253],"smartwatches.":[33],"The":[34,100,141,169,193],"goal":[35],"HAR":[37,95,112],"to":[39,43,114,129,135,173,224,265],"use":[40],"such":[41,53],"devices":[42],"assist":[44],"users":[45],"their":[47,266],"daily":[48],"lives":[49],"application":[51],"areas":[52],"as":[54,174],"healthcare,":[55],"physical":[56],"therapy,":[57],"fitness.":[59],"One":[60],"main":[63],"challenges":[64],"for":[65,77],"HAR,":[66],"particularly":[67],"when":[68],"supervised":[70],"learning":[71],"methods,":[72],"obtaining":[74],"balanced":[75],"algorithm":[78],"optimisation":[79],"testing.":[81],"As":[82],"people":[83],"perform":[84],"some":[85],"activities":[86],"more":[87,92,131],"than":[88,93,274],"others":[89,276],"(e.g.,":[90],"walk":[91],"run),":[94],"datasets":[96],"are":[97,162],"typically":[98],"imbalanced.":[99],"lack":[101],"dataset":[103],"representation":[104],"minority":[106,189],"classes":[107],"hinders":[108],"ability":[110],"classifiers":[113],"sufficiently":[115],"new":[117],"instances":[118],"those":[120],"activities.":[121],"We":[122,215,240],"introduce":[123],"three":[124,235],"novel":[125],"hybrid":[126,222],"sampling":[127,268],"strategies":[128],"generate":[130],"diverse":[132],"synthetic":[133,188],"samples":[134],"overcome":[136],"class":[138,251],"imbalance":[139,252],"problem.":[140],"first":[142],"strategy,":[143],"which":[144,161,196],"we":[145,197],"call":[146,198],"distance-based":[148],"method":[149,178,201],"(DBM),":[150],"combines":[151,180,203],"Synthetic":[152,205,211],"Minority":[153],"Oversampling":[154,206,212],"Techniques":[155],"(SMOTE)":[156],"with":[157],"Random_SMOTE,":[158],"both":[159],"built":[163],"around":[164],"k-nearest":[166],"neighbors":[167],"(KNN).":[168],"second":[170],"technique,":[171],"referred":[172],"noise":[176],"detection-based":[177],"(NDBM),":[179],"SMOTE":[181],"Tomek":[182],"links":[183],"(SMOTE_Tomeklinks)":[184],"modified":[187],"oversampling":[190],"technique":[191],"(MSMOTE).":[192],"third":[194],"approach,":[195],"cluster-based":[200],"(CBM),":[202],"Cluster-Based":[204],"(CBSO)":[207],"Proximity":[209],"Weighted":[210],"Technique":[213],"(ProWSyn).":[214],"compare":[216],"performance":[218],"proposed":[221],"methods":[223,228],"individual":[226],"constituent":[227,267],"baseline":[230],"accelerometer":[232],"commonly":[236],"used":[237],"benchmark":[238],"datasets.":[239],"show":[241],"that":[242],"DBM,":[243],"NDBM,":[244],"CBM":[246,270],"reduce":[247],"impact":[249],"enhance":[254],"F1":[255],"scores":[256],"a":[258,278],"range":[259],"9\u201320":[261],"percentage":[262],"point":[263],"compared":[264],"methods.":[269],"performs":[271],"significantly":[272],"better":[273],"under":[277],"Friedman":[279],"test,":[280],"however,":[281],"DBM":[282],"has":[283],"lower":[284],"computational":[285],"requirements.":[286]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}