{"id":"https://openalex.org/W4403839440","doi":"https://doi.org/10.1080/10618600.2024.2421248","title":"Multi-label Random Subspace Ensemble Classification","display_name":"Multi-label Random Subspace Ensemble Classification","publication_year":2024,"publication_date":"2024-10-28","ids":{"openalex":"https://openalex.org/W4403839440","doi":"https://doi.org/10.1080/10618600.2024.2421248","pmid":"https://pubmed.ncbi.nlm.nih.gov/40904727"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2421248","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2421248","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12404279/pdf/nihms-2032541.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101863813","display_name":"Bi Fan","orcid":"https://orcid.org/0000-0003-2193-6943"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fan Bi","raw_affiliation_strings":["Department of Biostatistics, New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058748996","display_name":"Jianan Zhu","orcid":"https://orcid.org/0000-0002-6582-7071"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianan Zhu","raw_affiliation_strings":["Department of Biostatistics, New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044345166","display_name":"Yang Feng","orcid":"https://orcid.org/0000-0001-7746-7598"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yang Feng","raw_affiliation_strings":["Department of Biostatistics, New York University"],"raw_orcid":"https://orcid.org/0000-0001-7746-7598","affiliations":[{"raw_affiliation_string":"Department of Biostatistics, New York University","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5044345166"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15853348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"3","first_page":"971","last_page":"983"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9988999962806702,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9988999962806702,"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":0.9886000156402588,"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":0.9843000173568726,"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/random-forest","display_name":"Random forest","score":0.7284078598022461},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.6808145642280579},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6711755394935608},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6545370817184448},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5973248481750488},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5966916084289551},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5793917775154114},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.5514411330223083},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5271387100219727},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4504561722278595},{"id":"https://openalex.org/keywords/multinomial-distribution","display_name":"Multinomial distribution","score":0.4261002540588379},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.4104244112968445},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40088289976119995},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3443876802921295},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23815476894378662},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11731499433517456}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7284078598022461},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.6808145642280579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6711755394935608},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6545370817184448},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5973248481750488},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5966916084289551},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5793917775154114},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.5514411330223083},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5271387100219727},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4504561722278595},{"id":"https://openalex.org/C192065140","wikidata":"https://www.wikidata.org/wiki/Q1147928","display_name":"Multinomial distribution","level":2,"score":0.4261002540588379},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.4104244112968445},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40088289976119995},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3443876802921295},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23815476894378662},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11731499433517456},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/10618600.2024.2421248","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2421248","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmid:40904727","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40904727","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":"Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:12404279","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12404279/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12404279/pdf/nihms-2032541.pdf","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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Comput Graph Stat","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:12404279","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12404279/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12404279/pdf/nihms-2032541.pdf","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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Comput Graph Stat","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2270921011","display_name":null,"funder_award_id":"1R21AG074205-01","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320319918","display_name":"York University","ror":"https://ror.org/05fq50484"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403839440.pdf","grobid_xml":"https://content.openalex.org/works/W4403839440.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W134960717","https://openalex.org/W216283022","https://openalex.org/W1526895711","https://openalex.org/W1753402186","https://openalex.org/W1800261609","https://openalex.org/W2057331441","https://openalex.org/W2076063813","https://openalex.org/W2105234758","https://openalex.org/W2113242816","https://openalex.org/W2118712128","https://openalex.org/W2143423446","https://openalex.org/W2562162676","https://openalex.org/W2798820905","https://openalex.org/W2895763047","https://openalex.org/W3010411193","https://openalex.org/W3016782972","https://openalex.org/W3034781939","https://openalex.org/W3102178346","https://openalex.org/W3172604113","https://openalex.org/W4206231027","https://openalex.org/W4233056867","https://openalex.org/W4236965008","https://openalex.org/W6608610325","https://openalex.org/W6631376643","https://openalex.org/W6637877409","https://openalex.org/W6698146022"],"related_works":["https://openalex.org/W2094490861","https://openalex.org/W1981866886","https://openalex.org/W2052615004","https://openalex.org/W2165937420","https://openalex.org/W2046975922","https://openalex.org/W4361733484","https://openalex.org/W4256395896","https://openalex.org/W2057416691","https://openalex.org/W1760344465","https://openalex.org/W2770076983"],"abstract_inverted_index":{"In":[0,58],"this":[1],"work,":[2],"we":[3],"develop":[4],"a":[5,19,36,68,108],"new":[6,147],"ensemble":[7],"learning":[8],"framework,":[9],"multi-label":[10,16],"Random":[11],"Subspace":[12],"Ensemble":[13],"(mRaSE),":[14],"for":[15],"classification.":[17],"Given":[18],"base":[20,76,111],"classifier":[21],"(e.g.,":[22],"multinomial":[23],"logistic":[24],"regression,":[25],"classification":[26,128],"tree,":[27],"K-nearest":[28],"neighbors),":[29],"mRaSE":[30,65,82],"works":[31],"by":[32],"first":[33],"randomly":[34],"sampling":[35],"collection":[37,109],"of":[38,81,110,155],"subspaces,":[39],"then":[40],"choosing":[41],"the":[42,47,54,74,89,97,102,116,120,126,156],"best":[43],"ones":[44],"that":[45],"achieve":[46],"minimum":[48],"cross-validation":[49],"errors":[50],"and,":[51],"finally,":[52],"aggregating":[53],"chosen":[55],"weak":[56],"learners.":[57],"addition":[59],"to":[60,86,101,115],"its":[61],"superior":[62],"prediction":[63],"performance,":[64],"also":[66,84],"provides":[67],"model-free":[69,92],"feature":[70],"ranking":[71],"depending":[72],"on":[73,96],"given":[75],"classifier.":[77],"An":[78],"iterative":[79,98],"version":[80,154],"is":[83,94],"developed":[85],"further":[87],"improve":[88],"performance.":[90],"A":[91],"extension":[93],"pursued":[95],"version,":[99],"leading":[100],"so-called":[103],"Super":[104],"mRaSE,":[105],"which":[106],"accepts":[107],"classifiers":[112],"as":[113],"input":[114],"algorithm.":[117],"We":[118],"show":[119],"proposed":[121],"algorithms":[122,148],"compared":[123],"favorably":[124],"with":[125],"state-of-the-art":[127],"algorithm":[129],"including":[130],"random":[131],"forest":[132],"and":[133,141],"deep":[134],"neural":[135],"network,":[136],"via":[137],"extensive":[138],"simulation":[139],"studies":[140],"two":[142],"real":[143],"data":[144],"applications.":[145],"The":[146],"are":[149],"implemented":[150],"in":[151],"an":[152],"updated":[153],"R":[157],"package":[158],"RaSEn.":[159]},"counts_by_year":[],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2024-10-29T00:00:00"}
