{"id":"https://openalex.org/W3144823608","doi":"https://doi.org/10.1108/dta-12-2020-0298","title":"A systematic review of machine learning-based missing value imputation techniques","display_name":"A systematic review of machine learning-based missing value imputation techniques","publication_year":2021,"publication_date":"2021-03-31","ids":{"openalex":"https://openalex.org/W3144823608","doi":"https://doi.org/10.1108/dta-12-2020-0298","mag":"3144823608"},"language":"en","primary_location":{"id":"doi:10.1108/dta-12-2020-0298","is_oa":false,"landing_page_url":"https://doi.org/10.1108/dta-12-2020-0298","pdf_url":null,"source":{"id":"https://openalex.org/S152623109","display_name":"Data Technologies and Applications","issn_l":"0033-0337","issn":["0033-0337","1758-7301","2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","raw_type":"journal-article"},"type":"review","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/A5036465646","display_name":"Tressy Thomas","orcid":"https://orcid.org/0000-0002-5270-5497"},"institutions":[{"id":"https://openalex.org/I10213569","display_name":"Cape Breton University","ror":"https://ror.org/052y05165","country_code":"CA","type":"education","lineage":["https://openalex.org/I10213569"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tressy Thomas","raw_affiliation_strings":["Shannon School of Business, Cape Breton University, Sydney, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5270-5497","affiliations":[{"raw_affiliation_string":"Shannon School of Business, Cape Breton University, Sydney, Canada","institution_ids":["https://openalex.org/I10213569"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021157841","display_name":"Enayat Rajabi","orcid":"https://orcid.org/0000-0002-9557-0043"},"institutions":[{"id":"https://openalex.org/I10213569","display_name":"Cape Breton University","ror":"https://ror.org/052y05165","country_code":"CA","type":"education","lineage":["https://openalex.org/I10213569"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Enayat Rajabi","raw_affiliation_strings":["Shannon School of Business, Cape Breton University, Sydney, Canada"],"raw_orcid":"https://orcid.org/0000-0002-9557-0043","affiliations":[{"raw_affiliation_string":"Shannon School of Business, Cape Breton University, Sydney, Canada","institution_ids":["https://openalex.org/I10213569"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10213569"],"apc_list":null,"apc_paid":null,"fwci":7.8644,"has_fulltext":false,"cited_by_count":100,"citation_normalized_percentile":{"value":0.98319328,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"55","issue":"4","first_page":"558","last_page":"585"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9800999760627747,"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/T13309","display_name":"Reliability and Agreement in Measurement","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.809933066368103},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7939244508743286},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6606638431549072},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5932294130325317},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5266081094741821},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.49411752820014954},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47393709421157837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4446410834789276},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3404023349285126},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.325996458530426},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20501908659934998}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.809933066368103},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7939244508743286},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6606638431549072},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5932294130325317},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5266081094741821},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.49411752820014954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47393709421157837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4446410834789276},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3404023349285126},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.325996458530426},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20501908659934998}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/dta-12-2020-0298","is_oa":false,"landing_page_url":"https://doi.org/10.1108/dta-12-2020-0298","pdf_url":null,"source":{"id":"https://openalex.org/S152623109","display_name":"Data Technologies and Applications","issn_l":"0033-0337","issn":["0033-0337","1758-7301","2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.46000000834465027,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":138,"referenced_works":["https://openalex.org/W386905621","https://openalex.org/W600012497","https://openalex.org/W612972800","https://openalex.org/W1485082296","https://openalex.org/W1488664896","https://openalex.org/W1495018677","https://openalex.org/W1580642020","https://openalex.org/W1598553907","https://openalex.org/W1837735658","https://openalex.org/W1970013111","https://openalex.org/W1971356345","https://openalex.org/W1977185509","https://openalex.org/W1982302025","https://openalex.org/W1984696633","https://openalex.org/W1984885482","https://openalex.org/W1989001380","https://openalex.org/W1993528069","https://openalex.org/W2011487780","https://openalex.org/W2013677212","https://openalex.org/W2031815538","https://openalex.org/W2032441932","https://openalex.org/W2034303004","https://openalex.org/W2062232660","https://openalex.org/W2064186732","https://openalex.org/W2074662725","https://openalex.org/W2084341220","https://openalex.org/W2096260291","https://openalex.org/W2100358124","https://openalex.org/W2102591093","https://openalex.org/W2112379925","https://openalex.org/W2127141904","https://openalex.org/W2154496386","https://openalex.org/W2156267802","https://openalex.org/W2162041599","https://openalex.org/W2166597282","https://openalex.org/W2176960823","https://openalex.org/W2181404312","https://openalex.org/W2192009965","https://openalex.org/W2198411115","https://openalex.org/W2273815808","https://openalex.org/W2295194552","https://openalex.org/W2316243772","https://openalex.org/W2337455698","https://openalex.org/W2346100606","https://openalex.org/W2390168739","https://openalex.org/W2397124290","https://openalex.org/W2407494999","https://openalex.org/W2473012037","https://openalex.org/W2480749004","https://openalex.org/W2483395546","https://openalex.org/W2501492680","https://openalex.org/W2541515526","https://openalex.org/W2549186529","https://openalex.org/W2552454876","https://openalex.org/W2559254298","https://openalex.org/W2568123413","https://openalex.org/W2579898249","https://openalex.org/W2589963520","https://openalex.org/W2590730823","https://openalex.org/W2590976943","https://openalex.org/W2594124327","https://openalex.org/W2603059385","https://openalex.org/W2626322442","https://openalex.org/W2703042647","https://openalex.org/W2763710617","https://openalex.org/W2765128980","https://openalex.org/W2793698072","https://openalex.org/W2797985113","https://openalex.org/W2803742393","https://openalex.org/W2805299991","https://openalex.org/W2885878606","https://openalex.org/W2886008386","https://openalex.org/W2889217298","https://openalex.org/W2890042675","https://openalex.org/W2890153472","https://openalex.org/W2891713324","https://openalex.org/W2892039641","https://openalex.org/W2892692020","https://openalex.org/W2894714913","https://openalex.org/W2894914645","https://openalex.org/W2897456403","https://openalex.org/W2898777818","https://openalex.org/W2900156484","https://openalex.org/W2900287961","https://openalex.org/W2900612779","https://openalex.org/W2900766238","https://openalex.org/W2900969174","https://openalex.org/W2901407647","https://openalex.org/W2902085258","https://openalex.org/W2903878011","https://openalex.org/W2904422417","https://openalex.org/W2905157535","https://openalex.org/W2905180125","https://openalex.org/W2905568531","https://openalex.org/W2911708802","https://openalex.org/W2913233426","https://openalex.org/W2922096583","https://openalex.org/W2924713973","https://openalex.org/W2932881901","https://openalex.org/W2935920497","https://openalex.org/W2945684222","https://openalex.org/W2947065948","https://openalex.org/W2949679216","https://openalex.org/W2950703937","https://openalex.org/W2953086467","https://openalex.org/W2954603179","https://openalex.org/W2955990193","https://openalex.org/W2961651406","https://openalex.org/W2964210632","https://openalex.org/W2969472744","https://openalex.org/W2969656600","https://openalex.org/W2972512804","https://openalex.org/W2978405342","https://openalex.org/W2979573534","https://openalex.org/W2980495984","https://openalex.org/W2980820631","https://openalex.org/W2981269376","https://openalex.org/W2982301445","https://openalex.org/W2988964633","https://openalex.org/W2990121693","https://openalex.org/W2990519679","https://openalex.org/W2995235877","https://openalex.org/W2996558251","https://openalex.org/W3002518602","https://openalex.org/W3005551496","https://openalex.org/W3007756963","https://openalex.org/W3008907608","https://openalex.org/W3009943557","https://openalex.org/W3015231783","https://openalex.org/W3015595300","https://openalex.org/W3018026180","https://openalex.org/W3027120276","https://openalex.org/W3033108443","https://openalex.org/W3102208177","https://openalex.org/W4233790333","https://openalex.org/W4240778236","https://openalex.org/W4245833769","https://openalex.org/W4256029126"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549","https://openalex.org/W3123177881"],"abstract_inverted_index":{"Purpose":[0],"The":[1,65,112,124,165,301],"primary":[2],"aim":[3],"of":[4,17,58,90,108,143,149,219,239,260,290,322,359,371,376,394,399],"this":[5,69,153,163,197],"study":[6,70,198,225],"is":[7,51,276,282,326,342,349,391],"to":[8,162,286,319,336,354,384,389,417],"review":[9,66,113,221,346],"the":[10,26,35,48,63,75,86,106,117,150,172,186,220,233,261,264,278,288,293,310,320,345,365,369,372,377,392,395,400],"studies":[11,262],"from":[12,267,344],"different":[13],"dimensions":[14],"including":[15],"type":[16,55],"methods,":[18],"experimentation":[19,87,330],"setup":[20],"and":[21,53,56,80,93,121,176,229,243,305,315,329,397,409,415],"evaluation":[22,107,252],"metrics":[23,102,253],"used":[24,104,216,251],"in":[25,34,62,68,97,171,203,217,254],"novel":[27],"approaches":[28,361],"proposed":[29,49,81,235],"for":[30,105,130,174,196,208],"data":[31,91,265,270,280,295,302,333,356,373],"imputation,":[32],"particularly":[33],"machine":[36],"learning":[37],"(ML)":[38],"area.":[39],"This":[40,201,224],"ultimately":[41],"provides":[42],"an":[43,158],"understanding":[44],"about":[45],"how":[46],"well":[47,363],"framework":[50],"evaluated":[52],"what":[54,73],"ratio":[57,307],"missingness":[59,94,306,366],"are":[60,71,74,95,168,193,199,215,232,249,317,413],"addressed":[61],"proposals.":[64],"questions":[67],"(1)":[72],"ML-based":[76],"imputation":[77,109,133,291],"methods":[78,378],"studied":[79],"during":[82],"2010\u20132020?":[83],"(2)":[84],"How":[85],"setup,":[88],"characteristics":[89,370],"sets":[92,266,296,334],"employed":[96],"these":[98,255],"studies?":[99],"(3)":[100],"What":[101],"were":[103,155,180],"method?":[110],"Design/methodology/approach":[111],"process":[114],"went":[115],"through":[116],"standard":[118],"identification,":[119],"screening":[120],"selection":[122],"process.":[123],"initial":[125],"search":[126],"on":[127,136,292,368,404],"electronic":[128],"databases":[129],"missing":[131,313,355],"value":[132],"(MVI)":[134],"based":[135,367,403],"ML":[137,360],"algorithms":[138,231,411],"returned":[139],"a":[140,327,338],"large":[141,332],"number":[142],"papers":[144,151,206,214],"totaling":[145],"at":[146,152],"2,883.":[147],"Most":[148,375],"stage":[154],"not":[156,194],"exactly":[157],"MVI":[159,236],"technique":[160],"relevant":[161],"study.":[164],"literature":[166,178,190],"reviews":[167,179,191],"first":[169],"scanned":[170],"title":[173],"relevancy,":[175],"306":[177],"identified":[181],"as":[182,284],"appropriate.":[183],"Upon":[184],"reviewing":[185],"abstract":[187],"text,":[188],"151":[189],"that":[192,227,277,347],"eligible":[195],"dropped.":[200],"resulted":[202],"155":[204],"research":[205],"suitable":[207],"full-text":[209],"review.":[210],"From":[211],"this,":[212],"117":[213],"assessment":[218],"questions.":[222],"Findings":[223],"shows":[226],"clustering-":[228],"instance-based":[230],"most":[234,250],"methods.":[237],"Percentage":[238],"correct":[240],"prediction":[241],"(PCP)":[242],"root":[244],"mean":[245],"square":[246],"error":[247],"(RMSE)":[248],"studies.":[256],"For":[257],"experimentation,":[258],"majority":[259],"sourced":[263],"publicly":[268],"available":[269],"set":[271,281,283,303],"repositories.":[272],"A":[273],"common":[274],"approach":[275],"complete":[279],"baseline":[285],"evaluate":[287],"effectiveness":[289],"test":[294],"with":[297,364,382],"artificially":[298],"induced":[299],"missingness.":[300],"size":[304],"varied":[308],"across":[309,422],"experimentations,":[311],"while":[312],"datatype":[314],"mechanism":[316],"pertaining":[318],"capability":[321],"imputation.":[323],"Computational":[324],"expense":[325],"concern,":[328],"using":[331],"appears":[335],"be":[337],"challenge.":[339],"Originality/value":[340],"It":[341],"understood":[343],"there":[348],"no":[350],"single":[351],"universal":[352],"solution":[353],"problem.":[357],"Variants":[358],"work":[362],"set.":[374],"reviewed":[379],"lack":[380],"generalization":[381],"regard":[383],"applicability.":[385],"Another":[386],"concern":[387],"related":[388],"applicability":[390],"complexity":[393],"formulation":[396],"implementation":[398],"algorithm.":[401],"Imputations":[402],"k":[405],"-nearest":[406],"neighbors":[407],"(kNN)":[408],"clustering":[410],"which":[412],"simple":[414],"easy":[416],"implement":[418],"make":[419],"it":[420],"popular":[421],"various":[423],"domains.":[424]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":34},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":5}],"updated_date":"2026-08-14T07:06:38.338062","created_date":"2025-10-10T00:00:00"}