{"id":"https://openalex.org/W2084701050","doi":"https://doi.org/10.1214/11-aoas495","title":"Prototype selection for interpretable classification","display_name":"Prototype selection for interpretable classification","publication_year":2011,"publication_date":"2011-12-01","ids":{"openalex":"https://openalex.org/W2084701050","doi":"https://doi.org/10.1214/11-aoas495","mag":"2084701050"},"language":"en","primary_location":{"id":"doi:10.1214/11-aoas495","doi":"https://doi.org/10.1214/11-aoas495","is_oa":false,"landing_page_url":"https://doi.org/10.1214/11-aoas495","pdf_url":null,"source":{"id":"https://openalex.org/S112778392","display_name":"The Annals of Applied Statistics","issn_l":"1932-6157","issn":["1932-6157","1941-7330"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","doyens","jufo-3","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319881","host_organization_name":"Institute of Mathematical Statistics","host_organization_lineage":["https://openalex.org/P4310319881"],"host_organization_lineage_names":["Institute of Mathematical Statistics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Annals of Applied Statistics","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W2084701050"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1202.5933","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076854744","display_name":"Jacob Bien","orcid":"https://orcid.org/0009-0006-7332-1325","observed_orcids":["https://orcid.org/0009-0006-7332-1325"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacob Bien","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027340494","display_name":"Robert John Tibshirani","orcid":"https://orcid.org/0000-0003-0553-5090","observed_orcids":["https://orcid.org/0000-0003-0553-5090"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert Tibshirani","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":1.9044,"has_fulltext":true,"cited_by_count":267,"citation_normalized_percentile":{"value":0.86839881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"5","issue":"4","first_page":"2403","last_page":"2424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.5249000191688538,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.5249000191688538,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.3472000062465668,"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/T13141","display_name":"Statistical Methods and Applications","score":0.034299999475479126,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prototype-selection","display_name":"prototype selection","score":0.9959999918937683},{"id":"https://openalex.org/keywords/interpretable-classification","display_name":"interpretable classification","score":0.8899999856948853},{"id":"https://openalex.org/keywords/nearest-neighbor-classification","display_name":"nearest neighbor classification","score":0.7170000076293945},{"id":"https://openalex.org/keywords/prototype-based-classifiers","display_name":"prototype-based classifiers","score":0.37599998712539673},{"id":"https://openalex.org/keywords/dissimilarity-measures","display_name":"dissimilarity measures","score":0.9070000052452087},{"id":"https://openalex.org/keywords/proteomics-data","display_name":"proteomics data","score":0.7570000290870667},{"id":"https://openalex.org/keywords/dataset-distillation","display_name":"dataset distillation","score":0.5429999828338623}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7294301986694336},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7211310863494873},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.5615823268890381},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5601997971534729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5268322825431824},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4586946368217468},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45394614338874817},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3735669255256653},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1214/11-aoas495","doi":"https://doi.org/10.1214/11-aoas495","is_oa":false,"landing_page_url":"https://doi.org/10.1214/11-aoas495","pdf_url":null,"source":{"id":"https://openalex.org/S112778392","display_name":"The Annals of Applied Statistics","issn_l":"1932-6157","issn":["1932-6157","1941-7330"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","doyens","jufo-3","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319881","host_organization_name":"Institute of Mathematical Statistics","host_organization_lineage":["https://openalex.org/P4310319881"],"host_organization_lineage_names":["Institute of Mathematical Statistics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Annals of Applied Statistics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1202.5933","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1202.5933","pdf_url":"https://arxiv.org/pdf/1202.5933","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.298.4970","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.298.4970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www-stat.stanford.edu/~jbien/aoas2011protoclass.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.752.2173","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.752.2173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1202.5933.pdf","raw_type":"text"},{"id":"pmh:oai:CULeuclid:euclid.aoas/1324399600","doi":null,"is_oa":false,"landing_page_url":"http://projecteuclid.org/euclid.aoas/1324399600","pdf_url":null,"source":{"id":"https://openalex.org/S4306400787","display_name":"Project Euclid (Cornell University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.48550/arxiv.1202.5933","doi":"https://doi.org/10.48550/arxiv.1202.5933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1202.5933","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1202.5933","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1202.5933","pdf_url":"https://arxiv.org/pdf/1202.5933","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G118171537","display_name":"Flexible and Adaptive Statistical Modeling","funder_award_id":"9971405","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G9000139216","display_name":null,"funder_award_id":"N01-HV-28183","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/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/W2084701050.pdf","grobid_xml":"https://content.openalex.org/works/W2084701050.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W608975221","https://openalex.org/W1480376833","https://openalex.org/W1511103935","https://openalex.org/W1587362683","https://openalex.org/W1679913846","https://openalex.org/W1969719708","https://openalex.org/W1974131786","https://openalex.org/W1991846872","https://openalex.org/W1994410331","https://openalex.org/W2018759642","https://openalex.org/W2075104607","https://openalex.org/W2097757574","https://openalex.org/W2101095383","https://openalex.org/W2122111042","https://openalex.org/W2122496402","https://openalex.org/W2130698119","https://openalex.org/W2135547590","https://openalex.org/W2137291015","https://openalex.org/W2138550913","https://openalex.org/W2142623187","https://openalex.org/W2143996311","https://openalex.org/W2148525712","https://openalex.org/W2166165501","https://openalex.org/W2168628284","https://openalex.org/W2168983954","https://openalex.org/W2170708028","https://openalex.org/W2170960297","https://openalex.org/W2175530190","https://openalex.org/W2611804663","https://openalex.org/W3120740533","https://openalex.org/W4206307172","https://openalex.org/W4235618170","https://openalex.org/W4294541781","https://openalex.org/W6679676526"],"related_works":["https://openalex.org/W1875666508","https://openalex.org/W2767571105","https://openalex.org/W2014403077","https://openalex.org/W2967518928","https://openalex.org/W199928093","https://openalex.org/W1844482222","https://openalex.org/W2803511684","https://openalex.org/W2138798794","https://openalex.org/W4410255853"],"abstract_inverted_index":{"Prototype":[0],"methods":[1],"seek":[2],"a":[3,12,18,33,37,76,107,118,138,155,180,205,216,232,251],"minimal":[4],"subset":[5],"of":[6,17,24,40,49,96,153,157,170,174,189],"samples":[7,42,88,223],"that":[8,104,203],"can":[9,173],"serve":[10],"as":[11,136,179,182,204],"distillation":[13],"or":[14,256],"condensed":[15],"view":[16],"data":[19,26,46,199,218],"set.":[20],"As":[21],"the":[22,45,72,82,87,150,164,168,186,193,213,222],"size":[23],"modern":[25],"sets":[27],"grows,":[28],"being":[29],"able":[30],"to":[31,215,246],"present":[32],"domain":[34],"specialist":[35],"with":[36,239],"short":[38],"list":[39],"\u201crepresentative\u201d":[41],"chosen":[43],"from":[44,100],"set":[47,110,119,156,169,200,219],"is":[48,98,115,133,237,254],"increasing":[50],"interpretative":[51,187],"value.":[52],"While":[53,130],"much":[54],"recent":[55],"statistical":[56],"research":[57],"has":[58],"been":[59],"focused":[60],"on":[61,167,192],"producing":[62,190],"sparse-in-the-variables":[63],"methods,":[64],"this":[65,146],"paper":[66,147],"aims":[67],"at":[68],"achieving":[69],"sparsity":[70],"in":[71,81,145,220,231,248],"samples.":[73],"We":[74,184,211],"discuss":[75,176],"method":[77,95,178,214,236],"for":[78],"selecting":[79],"prototypes":[80,191],"classification":[83],"setting":[84],"(in":[85],"which":[86,123,221,249],"fall":[89],"into":[90,117],"known":[91],"discrete":[92],"categories).":[93],"Our":[94,235],"focus":[97],"derived":[99],"three":[101],"basic":[102],"properties":[103],"we":[105,124,148,172],"believe":[106],"good":[108],"prototype":[109,131],"should":[111],"satisfy.":[112],"This":[113],"intuition":[114],"translated":[116],"cover":[120],"optimization":[121],"problem,":[122],"solve":[125],"approximately":[126],"using":[127,163,250],"standard":[128],"approaches.":[129],"selection":[132],"usually":[134],"viewed":[135],"purely":[137],"means":[139],"toward":[140],"building":[141],"an":[142],"efficient":[143],"classifier,":[144],"emphasize":[149],"inherent":[151],"value":[152,188],"having":[154],"prototypical":[158],"elements.":[159],"That":[160],"said,":[161],"by":[162],"nearest-neighbor":[165],"rule":[166],"prototypes,":[171],"course":[175],"our":[177],"classifier":[181,206],"well.":[183,210],"demonstrate":[185],"well-known":[194],"USPS":[195],"ZIP":[196],"code":[197],"digits":[198],"and":[201,226],"show":[202],"it":[207,244],"performs":[208],"reasonably":[209],"apply":[212],"proteomics":[217],"are":[224],"strings":[225],"therefore":[227],"not":[228],"naturally":[229],"embedded":[230],"vector":[233],"space.":[234],"compatible":[238],"any":[240],"dissimilarity":[241],"measure,":[242],"making":[243],"amenable":[245],"situations":[247],"non-Euclidean":[252],"metric":[253],"desirable":[255],"even":[257],"necessary.":[258]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":35},{"year":2022,"cited_by_count":37},{"year":2021,"cited_by_count":44},{"year":2020,"cited_by_count":27},{"year":2019,"cited_by_count":16},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":3}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2016-06-24T00:00:00"}