{"id":"https://openalex.org/W2953079191","doi":"https://doi.org/10.1007/s11634-019-00364-9","title":"Ensemble of optimal trees, random forest and random projection ensemble classification","display_name":"Ensemble of optimal trees, random forest and random projection ensemble classification","publication_year":2019,"publication_date":"2019-06-12","ids":{"openalex":"https://openalex.org/W2953079191","doi":"https://doi.org/10.1007/s11634-019-00364-9","mag":"2953079191"},"language":"en","primary_location":{"id":"doi:10.1007/s11634-019-00364-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-019-00364-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-019-00364-9.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"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":"Advances in Data Analysis and Classification","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11634-019-00364-9.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084849204","display_name":"Zardad Khan","orcid":"https://orcid.org/0000-0003-3933-9143"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]},{"id":"https://openalex.org/I181063083","display_name":"Abdul Wali Khan University Mardan","ror":"https://ror.org/03b9y4e65","country_code":"PK","type":"education","lineage":["https://openalex.org/I181063083"]}],"countries":["GB","PK"],"is_corresponding":true,"raw_author_name":"Zardad Khan","raw_affiliation_strings":["Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","Department of Statistics, Abdul Wali Khan University, Mardan, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","institution_ids":["https://openalex.org/I110002522"]},{"raw_affiliation_string":"Department of Statistics, Abdul Wali Khan University, Mardan, Pakistan","institution_ids":["https://openalex.org/I181063083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101885968","display_name":"Asma Gul","orcid":"https://orcid.org/0000-0003-1621-5447"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]},{"id":"https://openalex.org/I112819271","display_name":"Shaheed Benazir Bhutto Women University Peshawar","ror":"https://ror.org/00s2rk252","country_code":"PK","type":"education","lineage":["https://openalex.org/I112819271"]}],"countries":["GB","PK"],"is_corresponding":false,"raw_author_name":"Asma Gul","raw_affiliation_strings":["Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","Department of Statististics, Shaheed Benazir Bhutto Women University, Peshawar, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","institution_ids":["https://openalex.org/I110002522"]},{"raw_affiliation_string":"Department of Statististics, Shaheed Benazir Bhutto Women University, Peshawar, Pakistan","institution_ids":["https://openalex.org/I112819271"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090501466","display_name":"Aris Perperoglou","orcid":"https://orcid.org/0000-0003-1355-2800"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Aris Perperoglou","raw_affiliation_strings":["Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","institution_ids":["https://openalex.org/I110002522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081501425","display_name":"Miftahuddin Miftahuddin","orcid":"https://orcid.org/0000-0002-6414-4498"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]},{"id":"https://openalex.org/I187494767","display_name":"Universitas Syiah Kuala","ror":"https://ror.org/05v4dza81","country_code":"ID","type":"education","lineage":["https://openalex.org/I187494767"]}],"countries":["GB","ID"],"is_corresponding":false,"raw_author_name":"Miftahuddin Miftahuddin","raw_affiliation_strings":["College of Science, Syiah Kuala University, Banda Aceh, Indonesia","Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Science, Syiah Kuala University, Banda Aceh, Indonesia","institution_ids":["https://openalex.org/I187494767"]},{"raw_affiliation_string":"Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","institution_ids":["https://openalex.org/I110002522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061149601","display_name":"Osama Mahmoud","orcid":"https://orcid.org/0000-0003-0342-6704"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]},{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]},{"id":"https://openalex.org/I84058292","display_name":"Helwan University","ror":"https://ror.org/00h55v928","country_code":"EG","type":"education","lineage":["https://openalex.org/I84058292"]}],"countries":["EG","GB"],"is_corresponding":false,"raw_author_name":"Osama Mahmoud","raw_affiliation_strings":["Department of Applied Statistics, Helwan University, Cairo, Egypt","Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Statistics, Helwan University, Cairo, Egypt","institution_ids":["https://openalex.org/I84058292"]},{"raw_affiliation_string":"Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","institution_ids":["https://openalex.org/I110002522"]},{"raw_affiliation_string":"School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN, UK","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041953637","display_name":"Werner Adler","orcid":"https://orcid.org/0000-0001-9791-5407"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Werner Adler","raw_affiliation_strings":["Department of Biometry and Epidemiology, University of Erlangen-Nuremberg, Erlangen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biometry and Epidemiology, University of Erlangen-Nuremberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102819474","display_name":"Berthold Lausen","orcid":"https://orcid.org/0000-0002-0594-7258"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Berthold Lausen","raw_affiliation_strings":["Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK"],"raw_orcid":"https://orcid.org/0000-0002-0594-7258","affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK","institution_ids":["https://openalex.org/I110002522"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5084849204"],"corresponding_institution_ids":["https://openalex.org/I110002522","https://openalex.org/I181063083"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":5.5168,"has_fulltext":true,"cited_by_count":88,"citation_normalized_percentile":{"value":0.9661617,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"14","issue":"1","first_page":"97","last_page":"116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9919000267982483,"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/T10320","display_name":"Neural Networks and Applications","score":0.9919000267982483,"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":0.9897000193595886,"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/T10057","display_name":"Face and Expression Recognition","score":0.970300018787384,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.8899614810943604},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.7374409437179565},{"id":"https://openalex.org/keywords/brier-score","display_name":"Brier score","score":0.7312190532684326},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5722804665565491},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5674207806587219},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5564911365509033},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4907304048538208},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.4875871539115906},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4647957682609558},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.46212077140808105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4583986699581146},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45653921365737915},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.44992151856422424},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4356464147567749},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.42105773091316223},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3711061477661133},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36815786361694336},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3478611409664154},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21378982067108154}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8899614810943604},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.7374409437179565},{"id":"https://openalex.org/C35405484","wikidata":"https://www.wikidata.org/wiki/Q4967066","display_name":"Brier score","level":2,"score":0.7312190532684326},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5722804665565491},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5674207806587219},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5564911365509033},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4907304048538208},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.4875871539115906},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4647957682609558},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.46212077140808105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4583986699581146},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45653921365737915},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.44992151856422424},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4356464147567749},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.42105773091316223},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3711061477661133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36815786361694336},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3478611409664154},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21378982067108154},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11634-019-00364-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-019-00364-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-019-00364-9.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"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":"Advances in Data Analysis and Classification","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:advdac:v:14:y:2020:i:1:d:10.1007_s11634-019-00364-9","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s11634-019-00364-9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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"}],"best_oa_location":{"id":"doi:10.1007/s11634-019-00364-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-019-00364-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-019-00364-9.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"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":"Advances in Data Analysis and Classification","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G3482995644","display_name":"Smart Data Analytics for Business and Local Government","funder_award_id":"ES/L011859/1","funder_id":"https://openalex.org/F4320334630","funder_display_name":"Economic and Social Research Council"},{"id":"https://openalex.org/G7368362902","display_name":null,"funder_award_id":"ES/S007156/1","funder_id":"https://openalex.org/F4320334630","funder_display_name":"Economic and Social Research Council"},{"id":"https://openalex.org/G8322284704","display_name":null,"funder_award_id":"ES/L011859/1","funder_id":"https://openalex.org/F4320334630","funder_display_name":"Economic and Social Research Council"}],"funders":[{"id":"https://openalex.org/F4320334630","display_name":"Economic and Social Research Council","ror":"https://ror.org/03n0ht308"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2953079191.pdf","grobid_xml":"https://content.openalex.org/works/W2953079191.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W753132656","https://openalex.org/W1797580880","https://openalex.org/W1819522214","https://openalex.org/W1966280301","https://openalex.org/W1979279626","https://openalex.org/W1979753981","https://openalex.org/W2008667922","https://openalex.org/W2019778169","https://openalex.org/W2042614373","https://openalex.org/W2045053431","https://openalex.org/W2054418063","https://openalex.org/W2073241381","https://openalex.org/W2084481407","https://openalex.org/W2089898582","https://openalex.org/W2093717447","https://openalex.org/W2095015602","https://openalex.org/W2100805904","https://openalex.org/W2102201073","https://openalex.org/W2105234758","https://openalex.org/W2110501007","https://openalex.org/W2152761983","https://openalex.org/W2157963336","https://openalex.org/W2160207817","https://openalex.org/W2181164912","https://openalex.org/W2300264992","https://openalex.org/W2300934327","https://openalex.org/W2343608479","https://openalex.org/W2500600389","https://openalex.org/W2500727120","https://openalex.org/W2549551440","https://openalex.org/W2565649021","https://openalex.org/W2608839702","https://openalex.org/W2792447276","https://openalex.org/W2911964244","https://openalex.org/W3037729706","https://openalex.org/W3120740533","https://openalex.org/W6603861090"],"related_works":["https://openalex.org/W2794896638","https://openalex.org/W2891633941","https://openalex.org/W3136871737","https://openalex.org/W3202800081","https://openalex.org/W4252172277","https://openalex.org/W2558685994","https://openalex.org/W3101614107","https://openalex.org/W1909207154","https://openalex.org/W4390971112","https://openalex.org/W3036530763"],"abstract_inverted_index":{"The":[0],"predictive":[1],"performance":[2,78,158],"of":[3,14,21,25,45,117,144,159,206,219,223],"a":[4,22,61,101,224],"random":[5,138,167,169],"forest":[6,114],"ensemble":[7,108,140,208],"is":[8,33,103,209],"highly":[9],"associated":[10],"with":[11,166,241],"the":[12,43,65,71,87,97,106,113,118,157,160,193,196,204,207,220],"strength":[13],"individual":[15,77],"trees":[16,47,73,83,119],"and":[17,27,51,79,151,163,178,180,212],"their":[18,76],"diversity.":[19],"Ensemble":[20],"small":[23],"number":[24],"accurate":[26,50],"diverse":[28],"trees,":[29],"if":[30,109],"prediction":[31],"accuracy":[32],"not":[34,128],"compromised,":[35],"will":[36],"also":[37,228],"reduce":[38],"computational":[39],"burden.":[40],"We":[41,183],"investigate":[42],"idea":[44],"integrating":[46],"that":[48,120,203],"are":[49,153,215,227,235],"diverse.":[52],"For":[53],"this":[54],"purpose,":[55],"we":[56],"utilize":[57],"out-of-bag":[58],"observations":[59],"as":[60,137],"validation":[62,93],"sample":[63],"from":[64,96],"training":[66],"bootstrap":[67],"samples,":[68],"to":[69,112,155,237],"choose":[70],"best":[72,99],"based":[74],"on":[75,90,149,195],"then":[80],"assess":[81,156],"these":[82],"for":[84,105,134,191],"diversity":[85],"using":[86],"Brier":[88],"score":[89],"an":[91,130],"independent":[92],"sample.":[94],"Starting":[95],"first":[98],"tree,":[100],"tree":[102,136,232],"selected":[104],"final":[107],"its":[110],"addition":[111],"reduces":[115],"error":[116,189],"have":[121],"already":[122],"been":[123],"added.":[124],"Our":[125,200],"approach":[126],"does":[127],"use":[129],"implicit":[131],"dimension":[132],"reduction":[133],"each":[135],"project":[139],"classification.":[141],"A":[142],"total":[143],"35":[145],"bench":[146],"mark":[147],"problems":[148],"classification":[150,179,188],"regression":[152,181],"used":[154],"proposed":[161],"method":[162],"compare":[164],"it":[165],"forest,":[168],"projection":[170],"ensemble,":[171],"node":[172],"harvest,":[173],"support":[174],"vector":[175],"machine,":[176],"kNN":[177],"tree.":[182],"compute":[184],"unexplained":[185],"variances":[186],"or":[187],"rates":[190],"all":[192],"methods":[194],"corresponding":[197],"data":[198,239],"sets.":[199],"experiments":[201],"reveal":[202],"size":[205],"reduced":[210],"significantly":[211],"better":[213],"results":[214],"obtained":[216],"in":[217],"most":[218],"cases.":[221],"Results":[222],"simulation":[225],"study":[226],"given":[229],"where":[230],"four":[231],"style":[233],"scenarios":[234],"considered":[236],"generate":[238],"sets":[240],"several":[242],"structures.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":6}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
