{"id":"https://openalex.org/W2951544399","doi":"https://doi.org/10.1007/s10618-019-00638-y","title":"A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates","display_name":"A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates","publication_year":2019,"publication_date":"2019-06-17","ids":{"openalex":"https://openalex.org/W2951544399","doi":"https://doi.org/10.1007/s10618-019-00638-y","mag":"2951544399","pmid":"https://pubmed.ncbi.nlm.nih.gov/31632184"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-019-00638-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-019-00638-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-019-00638-y.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-019-00638-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081063163","display_name":"James Large","orcid":"https://orcid.org/0000-0002-2357-3798"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James Large","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"raw_orcid":"https://orcid.org/0000-0002-2357-3798","affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027003376","display_name":"Jason Lines","orcid":"https://orcid.org/0000-0002-1496-5941"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jason Lines","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"raw_orcid":"https://orcid.org/0000-0002-1496-5941","affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052586692","display_name":"Anthony Bagnall","orcid":"https://orcid.org/0000-0003-2360-8994"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Anthony Bagnall","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"raw_orcid":"https://orcid.org/0000-0003-2360-8994","affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5052586692"],"corresponding_institution_ids":["https://openalex.org/I1118541"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":7.4993,"has_fulltext":true,"cited_by_count":101,"citation_normalized_percentile":{"value":0.97615625,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"33","issue":"6","first_page":"1674","last_page":"1709"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9958000183105469,"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":0.9905999898910522,"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/weighting","display_name":"Weighting","score":0.6956853866577148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6877121329307556},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6589258313179016},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6556235551834106},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6299906969070435},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6096946001052856},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5848355889320374},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5752767324447632},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5326024889945984},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5131178498268127},{"id":"https://openalex.org/keywords/probabilistic-classification","display_name":"Probabilistic classification","score":0.47200489044189453},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3507205843925476},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.25345802307128906}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6956853866577148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6877121329307556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6589258313179016},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6556235551834106},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6299906969070435},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6096946001052856},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5848355889320374},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5752767324447632},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5326024889945984},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5131178498268127},{"id":"https://openalex.org/C189119545","wikidata":"https://www.wikidata.org/wiki/Q5128022","display_name":"Probabilistic classification","level":4,"score":0.47200489044189453},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3507205843925476},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.25345802307128906},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s10618-019-00638-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-019-00638-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-019-00638-y.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},{"id":"pmid:31632184","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31632184","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":"Data mining and knowledge discovery","raw_type":null},{"id":"pmh:oai:ueaeprints.uea.ac.uk:71086","is_oa":true,"landing_page_url":null,"pdf_url":"https://ueaeprints.uea.ac.uk/id/eprint/71086/1/main.pdf","source":{"id":"https://openalex.org/S4306400384","display_name":"UEA Digital Repository (University of East Anglia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1118541","host_organization_name":"University of East Anglia","host_organization_lineage":["https://openalex.org/I1118541"],"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":"Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:6790343","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6790343","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":"Data Min Knowl Discov","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s10618-019-00638-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-019-00638-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-019-00638-y.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.550000011920929}],"awards":[{"id":"https://openalex.org/G1289431254","display_name":null,"funder_award_id":"M011216","funder_id":"https://openalex.org/F4320334629","funder_display_name":"Biotechnology and Biological Sciences Research Council"},{"id":"https://openalex.org/G2343858269","display_name":null,"funder_award_id":"1786465","funder_id":"https://openalex.org/F4320334629","funder_display_name":"Biotechnology and Biological Sciences Research Council"},{"id":"https://openalex.org/G3087056252","display_name":null,"funder_award_id":"EP/M015807/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G4333889053","display_name":"The Norwich Research Park Biosciences Doctoral Training Partnership","funder_award_id":"BB/M011216/1","funder_id":"https://openalex.org/F4320334629","funder_display_name":"Biotechnology and Biological Sciences Research Council"},{"id":"https://openalex.org/G6504804383","display_name":"Machine learning algorithms for detecting forged alcohol","funder_award_id":"1786465","funder_id":"https://openalex.org/F4320334629","funder_display_name":"Biotechnology and Biological Sciences Research Council"},{"id":"https://openalex.org/G6739827899","display_name":"The Collective of Transform Ensembles (COTE) for Time Series Classification","funder_award_id":"EP/M015807/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G7315120509","display_name":null,"funder_award_id":"E/M015807/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320320274","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93"},{"id":"https://openalex.org/F4320332167","display_name":"Directorate for Biological Sciences","ror":"https://ror.org/001xhss06"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320334629","display_name":"Biotechnology and Biological Sciences Research Council","ror":"https://ror.org/00cwqg982"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2951544399.pdf","grobid_xml":"https://content.openalex.org/works/W2951544399.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W13924619","https://openalex.org/W28412257","https://openalex.org/W67158865","https://openalex.org/W1509515766","https://openalex.org/W1565746575","https://openalex.org/W1582036668","https://openalex.org/W1605688901","https://openalex.org/W1645816215","https://openalex.org/W1652465939","https://openalex.org/W1678356000","https://openalex.org/W1680392829","https://openalex.org/W1693343509","https://openalex.org/W1731081199","https://openalex.org/W1806891645","https://openalex.org/W1980264541","https://openalex.org/W1988844742","https://openalex.org/W2004918970","https://openalex.org/W2023294425","https://openalex.org/W2024046085","https://openalex.org/W2035104901","https://openalex.org/W2056132907","https://openalex.org/W2097998348","https://openalex.org/W2099715980","https://openalex.org/W2100805904","https://openalex.org/W2106525823","https://openalex.org/W2108949035","https://openalex.org/W2109553965","https://openalex.org/W2112076978","https://openalex.org/W2113242816","https://openalex.org/W2113599721","https://openalex.org/W2115629999","https://openalex.org/W2122892819","https://openalex.org/W2135293965","https://openalex.org/W2148771442","https://openalex.org/W2150757437","https://openalex.org/W2158275940","https://openalex.org/W2163605009","https://openalex.org/W2168046285","https://openalex.org/W2169284845","https://openalex.org/W2171752105","https://openalex.org/W2295598076","https://openalex.org/W2335925837","https://openalex.org/W2440222035","https://openalex.org/W2481897712","https://openalex.org/W2490023472","https://openalex.org/W2524083015","https://openalex.org/W2531563875","https://openalex.org/W2555077524","https://openalex.org/W2557740646","https://openalex.org/W2590507395","https://openalex.org/W2605316438","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W2950533047","https://openalex.org/W2963839817","https://openalex.org/W2998768810","https://openalex.org/W3100344990","https://openalex.org/W3102476541","https://openalex.org/W4237706399"],"related_works":["https://openalex.org/W4224922629","https://openalex.org/W2177788029","https://openalex.org/W2038224889","https://openalex.org/W1957831838","https://openalex.org/W1861738855","https://openalex.org/W4312017181","https://openalex.org/W4385147326","https://openalex.org/W2555325751","https://openalex.org/W2085597081","https://openalex.org/W2149131139"],"abstract_inverted_index":{"Our":[0],"hypothesis":[1],"is":[2,109,185,245],"that":[3,108,130,159,182,223,243],"building":[4,34],"ensembles":[5,37,116],"of":[6,9,45,52,73,99,133,147,207,214,218],"small":[7,35,71],"sets":[8],"strong":[10,231],"classifiers":[11,48,103,120,232],"constructed":[12],"with":[13,49,190,233],"different":[14],"learning":[15],"algorithms":[16],"is,":[17,225],"on":[18,39,58,121,226],"average,":[19,227],"the":[20,42,46,53,59,69,124,131,134,149,166,175,183,205,208,211,219],"best":[21],"approach":[22],"to":[23,90,142,203,229],"classification":[24,153],"for":[25,33,169,250],"real-world":[26],"problems.":[27],"We":[28,62,93,127,173,194,221],"propose":[29],"a":[30,143,196,234,246],"simple":[31],"mechanism":[32],"heterogeneous":[36,91],"based":[38],"exponentially":[40],"weighting":[41,235],"probability":[43],"estimates":[44],"base":[47,74],"an":[50,97,106,200],"estimate":[51],"accuracy":[54,136],"formed":[55],"through":[56,64],"cross-validation":[57,135],"train":[60,192],"data.":[61],"demonstrate":[63,158,204],"extensive":[65,240],"experimentation":[66],"that,":[67],"given":[68],"same":[70],"set":[72,146],"classifiers,":[75],"this":[76,170],"method":[77],"has":[78],"measurable":[79],"benefits":[80],"over":[81],"commonly":[82],"used":[83],"alternative":[84],"weighting,":[85],"selection":[86],"or":[87],"meta-classifier":[88],"approaches":[89],"ensembles.":[92],"also":[94,157],"show":[95],"how":[96],"ensemble":[98,107,139,161,209,230],"five":[100],"well-known,":[101],"fast":[102],"can":[104,163],"produce":[105],"not":[110],"significantly":[111,164],"worse":[112],"than":[113,238],"large":[114],"homogeneous":[115],"and":[117,155,180,199,210,242],"tuned":[118],"individual":[119],"datasets":[122],"from":[123],"UCI":[125],"archive.":[126],"provide":[128],"evidence":[129],"performance":[132,176],"weighted":[137],"probabilistic":[138],"(CAWPE)":[140],"generalises":[141],"completely":[144],"separate":[145],"datasets,":[148],"UCR":[150],"time":[151],"series":[152],"archive,":[154],"we":[156],"our":[160],"technique":[162],"improve":[165],"state-of-the-art":[167],"classifier":[168],"problem":[171],"domain.":[172],"investigate":[174],"in":[177,188],"more":[178],"detail,":[179],"find":[181],"improvement":[184],"most":[186],"marked":[187],"problems":[189],"smaller":[191],"sets.":[193],"perform":[195,239],"sensitivity":[197],"analysis":[198],"ablation":[201],"study":[202],"robustness":[206],"significant":[212],"contribution":[213],"each":[215],"design":[216],"element":[217],"classifier.":[220],"conclude":[222],"it":[224],"better":[228],"scheme":[236],"rather":[237],"tuning":[241],"CAWPE":[244],"sensible":[247],"starting":[248],"point":[249],"combining":[251],"classifiers.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}