{"id":"https://openalex.org/W3204938259","doi":"https://doi.org/10.1093/comjnl/bxab138","title":"Mean Error Rate Weighted Online Boosting Method","display_name":"Mean Error Rate Weighted Online Boosting Method","publication_year":2021,"publication_date":"2021-09-08","ids":{"openalex":"https://openalex.org/W3204938259","doi":"https://doi.org/10.1093/comjnl/bxab138","mag":"3204938259"},"language":"en","primary_location":{"id":"doi:10.1093/comjnl/bxab138","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxab138","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","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/A5080393871","display_name":"Nagaraj Honnikoll","orcid":"https://orcid.org/0000-0001-9953-5598"},"institutions":[{"id":"https://openalex.org/I110083240","display_name":"Karnatak University","ror":"https://ror.org/05ajnv358","country_code":"IN","type":"education","lineage":["https://openalex.org/I110083240"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nagaraj Honnikoll","raw_affiliation_strings":["Department of Computer Science , Karnatak University, Karnataka 580003, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Karnatak University, Karnataka 580003, India","institution_ids":["https://openalex.org/I110083240"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016175867","display_name":"Ishwar Baidari","orcid":"https://orcid.org/0000-0002-3628-3546"},"institutions":[{"id":"https://openalex.org/I110083240","display_name":"Karnatak University","ror":"https://ror.org/05ajnv358","country_code":"IN","type":"education","lineage":["https://openalex.org/I110083240"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ishwar Baidari","raw_affiliation_strings":["Department of Computer Science , Karnatak University, Karnataka 580003, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Karnatak University, Karnataka 580003, India","institution_ids":["https://openalex.org/I110083240"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5016175867"],"corresponding_institution_ids":["https://openalex.org/I110083240"],"apc_list":{"value":2877,"currency":"GBP","value_usd":3794},"apc_paid":null,"fwci":0.269,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65780236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"66","issue":"1","first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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":0.9973999857902527,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9950000047683716,"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/boosting","display_name":"Boosting (machine learning)","score":0.9610283970832825},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7528414726257324},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.650894045829773},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6423612833023071},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.567714512348175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.538627028465271},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.42336001992225647},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.418887734413147},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34398967027664185},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15902063250541687},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14519569277763367},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.10409817099571228}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.9610283970832825},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7528414726257324},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.650894045829773},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6423612833023071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.567714512348175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.538627028465271},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.42336001992225647},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.418887734413147},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34398967027664185},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15902063250541687},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14519569277763367},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.10409817099571228}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/comjnl/bxab138","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxab138","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8500000238418579}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W163595754","https://openalex.org/W1565746575","https://openalex.org/W1578080815","https://openalex.org/W1585854823","https://openalex.org/W1931284523","https://openalex.org/W1979675141","https://openalex.org/W1984308372","https://openalex.org/W1988790447","https://openalex.org/W2016023958","https://openalex.org/W2016159616","https://openalex.org/W2019458237","https://openalex.org/W2022851810","https://openalex.org/W2049963988","https://openalex.org/W2070534370","https://openalex.org/W2073256825","https://openalex.org/W2093825590","https://openalex.org/W2094047042","https://openalex.org/W2097178527","https://openalex.org/W2123003172","https://openalex.org/W2135335717","https://openalex.org/W2156357252","https://openalex.org/W2171809276","https://openalex.org/W2343742239","https://openalex.org/W2495221668","https://openalex.org/W2556012038","https://openalex.org/W2602645338","https://openalex.org/W2607662938","https://openalex.org/W2890607711","https://openalex.org/W2908746407","https://openalex.org/W2912083425","https://openalex.org/W2919663631","https://openalex.org/W2941258581","https://openalex.org/W2947225536","https://openalex.org/W2958316025","https://openalex.org/W2977431930","https://openalex.org/W3003253354","https://openalex.org/W4212883601","https://openalex.org/W4244952642","https://openalex.org/W4252185853","https://openalex.org/W4297944103","https://openalex.org/W4299828299","https://openalex.org/W4366658060","https://openalex.org/W6633774736","https://openalex.org/W6680192438","https://openalex.org/W6685747873"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W2885516856","https://openalex.org/W4289703016","https://openalex.org/W4310224730","https://openalex.org/W4296079469"],"abstract_inverted_index":{"Abstract":[0],"Boosting":[1],"is":[2,53],"a":[3,9,15,54],"generally":[4],"known":[5],"technique":[6,49],"to":[7,39,59,64,88,96],"convert":[8],"group":[10],"of":[11,47,80,84,93,101,109],"weak":[12],"learners":[13,87],"into":[14],"powerful":[16],"ensemble.":[17],"To":[18,44],"reach":[19],"this":[20],"desired":[21],"objective":[22],"successfully,":[23],"the":[24,33,61,94,99,110,112,119],"modules":[25],"are":[26,35],"trained":[27],"with":[28],"distinct":[29],"data":[30],"samples":[31],"and":[32],"hypotheses":[34],"combined":[36],"in":[37,50,67,107],"order":[38],"achieve":[40,89],"an":[41],"optimal":[42],"prediction.":[43],"make":[45,78],"use":[46,79],"boosting":[48,75],"online":[51,74],"condition":[52],"new":[55,73],"approach.":[56],"It":[57],"motivates":[58],"meet":[60],"requirements":[62],"due":[63],"its":[65],"success":[66],"offline":[68],"conditions.":[69],"This":[70],"work":[71],"presents":[72],"method.":[76],"We":[77],"mean":[81],"error":[82],"rate":[83],"individual":[85],"base":[86],"effective":[90],"weight":[91],"distribution":[92],"instances":[95],"closely":[97],"match":[98],"behavior":[100],"OzaBoost.":[102],"Experimental":[103],"results":[104],"show":[105],"that,":[106],"most":[108],"situations,":[111],"proposed":[113],"method":[114],"achieves":[115],"better":[116],"accuracies,":[117],"outperforming":[118],"other":[120],"state-of-art":[121],"methods.":[122]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
