{"id":"https://openalex.org/W4403420636","doi":"https://doi.org/10.1109/mipr62202.2024.00051","title":"Unveiling Statistical Significance of Online Regression Over Multiple Datasets","display_name":"Unveiling Statistical Significance of Online Regression Over Multiple Datasets","publication_year":2024,"publication_date":"2024-08-07","ids":{"openalex":"https://openalex.org/W4403420636","doi":"https://doi.org/10.1109/mipr62202.2024.00051"},"language":"en","primary_location":{"id":"doi:10.1109/mipr62202.2024.00051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mipr62202.2024.00051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR)","raw_type":"proceedings-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/A5092427258","display_name":"Mohammad Abu-Shaira","orcid":"https://orcid.org/0009-0008-2241-0373"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohammad Abu-Shaira","raw_affiliation_strings":["The University of North Texas,Computer Science and Engineering,Denton,United States"],"affiliations":[{"raw_affiliation_string":"The University of North Texas,Computer Science and Engineering,Denton,United States","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035107019","display_name":"Weishi Shi","orcid":"https://orcid.org/0000-0002-4863-1464"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weishi Shi","raw_affiliation_strings":["The University of North Texas,Computer Science and Engineering,Denton,United States"],"affiliations":[{"raw_affiliation_string":"The University of North Texas,Computer Science and Engineering,Denton,United States","institution_ids":["https://openalex.org/I123534392"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5092427258"],"corresponding_institution_ids":["https://openalex.org/I123534392"],"apc_list":null,"apc_paid":null,"fwci":0.7823,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.79772877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"274","last_page":"279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.86080002784729,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11644","display_name":"Spam and Phishing Detection","score":0.86080002784729,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.781000018119812,"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":0.6278576254844666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45696017146110535},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4527937173843384},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.43710675835609436},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3598506450653076},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29809969663619995},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16688451170921326}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6278576254844666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45696017146110535},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4527937173843384},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.43710675835609436},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3598506450653076},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29809969663619995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16688451170921326}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mipr62202.2024.00051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mipr62202.2024.00051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W25574983","https://openalex.org/W1535810436","https://openalex.org/W1635892993","https://openalex.org/W1857789879","https://openalex.org/W1974758710","https://openalex.org/W2004108172","https://openalex.org/W2059700429","https://openalex.org/W2074292461","https://openalex.org/W2145012531","https://openalex.org/W2490805536","https://openalex.org/W2577511304","https://openalex.org/W2997546679","https://openalex.org/W3009009611","https://openalex.org/W3118299338","https://openalex.org/W3159649695","https://openalex.org/W4210572675","https://openalex.org/W4247196369","https://openalex.org/W6683584131","https://openalex.org/W6779294953","https://openalex.org/W6862989276"],"related_works":["https://openalex.org/W4381136829","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125"],"abstract_inverted_index":{"Despite":[0],"extensive":[1],"focus":[2],"on":[3,13],"techniques":[4],"for":[5,58,170],"evaluating":[6],"the":[7,17,42,78,91,113,147],"performance":[8,81,148],"of":[9,20,44,80,149,175],"two":[10],"learning":[11,38,55],"algorithms":[12,27],"a":[14,68],"single":[15],"dataset,":[16],"critical":[18],"challenge":[19],"developing":[21],"statistical":[22,48,72,160],"tests":[23,144],"to":[24,52,76],"compare":[25,103],"multiple":[26,104],"across":[28,108,139],"various":[29,109,140],"datasets":[30,129],"has":[31],"been":[32],"largely":[33],"overlooked":[34],"in":[35,41,67,172],"most":[36],"machine":[37],"research.":[39],"Additionally,":[40],"realm":[43],"Online":[45],"Learning,":[46],"ensuring":[47],"significance":[49,79],"is":[50,167],"essential":[51],"validate":[53],"continuous":[54],"processes,":[56],"particularly":[57],"achieving":[59],"rapid":[60],"convergence":[61],"and":[62,96,127,133],"effectively":[63],"managing":[64],"concept":[65],"drifts":[66],"timely":[69],"manner.":[70],"Robust":[71],"methods":[73],"are":[74],"needed":[75],"assess":[77],"differences":[82],"as":[83,152],"data":[84,141],"evolves":[85],"over":[86],"time.":[87],"This":[88],"article":[89],"examines":[90],"state-of-the-art":[92,176],"online":[93,105],"regression":[94,106],"models":[95,107],"empirically":[97],"evaluates":[98],"several":[99],"suitable":[100],"tests.":[101,120],"To":[102],"datasets,":[110],"we":[111],"employed":[112],"Friedman":[114],"test":[115,161],"along":[116],"with":[117,130,154],"corresponding":[118],"post-hoc":[119],"For":[121],"thorough":[122],"evaluations,":[123],"utilizing":[124],"both":[125],"real":[126],"synthetic":[128],"5-fold":[131],"cross-validation":[132],"seed":[134],"averaging":[135],"ensures":[136],"comprehensive":[137],"assessment":[138],"subsets.":[142],"Our":[143],"generally":[145],"confirmed":[146],"competitive":[150],"baselines":[151],"consistent":[153],"their":[155],"individual":[156],"reports.":[157],"However,":[158],"some":[159],"results":[162],"also":[163],"indicate":[164],"that":[165],"there":[166],"still":[168],"room":[169],"improvement":[171],"certain":[173],"aspects":[174],"methods.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
