{"id":"https://openalex.org/W2066250318","doi":"https://doi.org/10.1080/03610910802513214","title":"New Bootstrap Applications in Supervised Learning","display_name":"New Bootstrap Applications in Supervised Learning","publication_year":2008,"publication_date":"2008-12-12","ids":{"openalex":"https://openalex.org/W2066250318","doi":"https://doi.org/10.1080/03610910802513214","mag":"2066250318"},"language":"en","primary_location":{"id":"doi:10.1080/03610910802513214","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910802513214","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","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/A5035010764","display_name":"Get\u00falio Jos\u00e9 Amorim do Amaral","orcid":"https://orcid.org/0000-0002-4129-1508"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Getulio Jose Amorim Amaral","raw_affiliation_strings":["Department of Statistics , Federal University of Pernambuco , Pernambuco, Brazil"],"affiliations":[{"raw_affiliation_string":"Department of Statistics , Federal University of Pernambuco , Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025429430","display_name":"Marcelo R.P. Ferreira","orcid":"https://orcid.org/0000-0003-0242-0255"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marcelo Rodrigo Portela Ferreira","raw_affiliation_strings":["Department of Statistics , Federal University of Pernambuco , Pernambuco, Brazil"],"affiliations":[{"raw_affiliation_string":"Department of Statistics , Federal University of Pernambuco , Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035010764"],"corresponding_institution_ids":["https://openalex.org/I25112270"],"apc_list":null,"apc_paid":null,"fwci":0.3512,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63713117,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"2","first_page":"416","last_page":"425"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.996399998664856,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.996399998664856,"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"}},{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9904999732971191,"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":0.8813623189926147},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6454656720161438},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5764299631118774},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5597262978553772},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5596113204956055},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5401015281677246},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.41987305879592896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3563755750656128},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3552771210670471},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22474589943885803},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.07154533267021179}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8813623189926147},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6454656720161438},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5764299631118774},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5597262978553772},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5596113204956055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5401015281677246},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.41987305879592896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3563755750656128},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3552771210670471},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22474589943885803},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.07154533267021179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910802513214","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910802513214","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.75}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323678","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Ci\u00eancia e Tecnologia do Estado de Pernambuco","ror":"https://ror.org/02te5rf52"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1486484638","https://openalex.org/W1979159029","https://openalex.org/W1988790447","https://openalex.org/W1995945562","https://openalex.org/W2001619934","https://openalex.org/W2024046085","https://openalex.org/W2024161327","https://openalex.org/W2040615655","https://openalex.org/W2060143287","https://openalex.org/W2097879961","https://openalex.org/W2112076978","https://openalex.org/W2117897510","https://openalex.org/W2127314075","https://openalex.org/W2168123127","https://openalex.org/W3106889297","https://openalex.org/W4212865292","https://openalex.org/W4237650020","https://openalex.org/W4243562335","https://openalex.org/W4250236131","https://openalex.org/W4255806375","https://openalex.org/W4298872162","https://openalex.org/W6676769703"],"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/W3094138326","https://openalex.org/W4310224730"],"abstract_inverted_index":{"Some":[0],"bootstrap":[1,25],"and":[2],"boosting":[3,20,44],"methods":[4,81],"for":[5,43],"problems":[6],"related":[7],"to":[8,35],"classification":[9,38],"are":[10],"introduced":[11],"in":[12,45,52,84],"this":[13,53],"article.":[14],"The":[15,28],"first":[16],"method":[17,30],"chooses":[18],"better":[19],"weights":[21],"by":[22,60],"using":[23],"a":[24,32,37],"search":[26],"algorithm.":[27],"second":[29],"is":[31,49,58,66],"good":[33],"way":[34],"define":[36],"frontier.":[39],"A":[40],"new":[41,54],"formulation":[42,55],"linear":[46],"discriminant":[47],"analysis":[48],"given.":[50],"Since":[51],"the":[56,61,70,79],"uncertainty":[57],"represented":[59],"weighted":[62],"covariance":[63],"matrix,":[64],"it":[65],"more":[67],"appropriate":[68],"from":[69],"conceptual":[71],"point":[72],"of":[73],"view.":[74],"Simulation":[75],"results":[76],"show":[77],"that":[78],"proposed":[80],"perform":[82],"well":[83],"data":[85],"analysis.":[86]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
