{"id":"https://openalex.org/W2001834133","doi":"https://doi.org/10.1109/ssp.2012.6319812","title":"A bootstrap interval estimator for Bayes' classification error","display_name":"A bootstrap interval estimator for Bayes' classification error","publication_year":2012,"publication_date":"2012-08-01","ids":{"openalex":"https://openalex.org/W2001834133","doi":"https://doi.org/10.1109/ssp.2012.6319812","mag":"2001834133"},"language":"en","primary_location":{"id":"doi:10.1109/ssp.2012.6319812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2012.6319812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-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/A5057520613","display_name":"Chad M. Hawes","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chad M. Hawes","raw_affiliation_strings":["Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA","Johns Hopkins University, Department of Applied Mathematics and Statistics, Baltimore, MD 21218, USA"],"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Johns Hopkins University, Department of Applied Mathematics and Statistics, Baltimore, MD 21218, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031834098","display_name":"Carey E. Priebe","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carey E. Priebe","raw_affiliation_strings":["Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA","Johns Hopkins University, Department of Applied Mathematics and Statistics, Baltimore, MD 21218, USA"],"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Johns Hopkins University, Department of Applied Mathematics and Statistics, Baltimore, MD 21218, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057520613"],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08451224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":null,"first_page":"748","last_page":"751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9994999766349792,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9994999766349792,"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":0.9976999759674072,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9962000250816345,"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/bayes-error-rate","display_name":"Bayes error rate","score":0.814642071723938},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.723561704158783},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6469968557357788},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.6240091919898987},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.5536167621612549},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5474803447723389},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5143455266952515},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5074009299278259},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4919595420360565},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.48761239647865295},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.46827247738838196},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.4161544442176819},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3896086812019348},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3828029930591583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27319228649139404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.25731319189071655},{"id":"https://openalex.org/keywords/bayes-classifier","display_name":"Bayes classifier","score":0.22500327229499817},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.19562649726867676},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.16170614957809448},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.07783651351928711},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.07540687918663025}],"concepts":[{"id":"https://openalex.org/C143809311","wikidata":"https://www.wikidata.org/wiki/Q4874458","display_name":"Bayes error rate","level":5,"score":0.814642071723938},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.723561704158783},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6469968557357788},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.6240091919898987},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.5536167621612549},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5474803447723389},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5143455266952515},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5074009299278259},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4919595420360565},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.48761239647865295},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.46827247738838196},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4161544442176819},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3896086812019348},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3828029930591583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27319228649139404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.25731319189071655},{"id":"https://openalex.org/C185207860","wikidata":"https://www.wikidata.org/wiki/Q17004744","display_name":"Bayes classifier","level":4,"score":0.22500327229499817},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.19562649726867676},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.16170614957809448},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.07783651351928711},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07540687918663025},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ssp.2012.6319812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2012.6319812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.648.9058","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.648.9058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ams.jhu.edu/~priebe/.FILES/BootstrapIntervalEstimator_forBayesOptimalError_SSP_Final-1.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1564947197","https://openalex.org/W1981190555","https://openalex.org/W1989584148","https://openalex.org/W2005646879","https://openalex.org/W2035981651","https://openalex.org/W2042770250","https://openalex.org/W2075381171","https://openalex.org/W2088779313","https://openalex.org/W2097197066","https://openalex.org/W2098374505","https://openalex.org/W2134177842","https://openalex.org/W2163817918","https://openalex.org/W3120740533","https://openalex.org/W6674177778"],"related_works":["https://openalex.org/W2374047926","https://openalex.org/W179179905","https://openalex.org/W2394466068","https://openalex.org/W2360982908","https://openalex.org/W2086147528","https://openalex.org/W2393473353","https://openalex.org/W1973600295","https://openalex.org/W2537862391","https://openalex.org/W1599512561","https://openalex.org/W2042770250"],"abstract_inverted_index":{"Using":[0,74],"a":[1,7,44,54,75,112,127],"finite-length":[2,38,128],"training":[3,30,40,57,129],"set,":[4],"we":[5,79],"propose":[6],"new":[8],"estimation":[9],"approach":[10],"suitable":[11],"as":[12,53],"an":[13,93,120],"interval":[14,122],"estimate":[15,26,123],"of":[16,32,56,124],"the":[17,36,49,63,85],"Bayes-optimal":[18],"classification":[19,137],"error":[20,51,67,141],"L*.":[21,116],"We":[22,42,131],"arrive":[23],"at":[24],"this":[25,71,81],"by":[27],"constructing":[28],"bootstrap":[29,64],"sets":[31],"varying":[33],"size":[34,59],"from":[35,77,126],"fixed,":[37],"original":[39],"set.":[41],"assume":[43],"power-law":[45,72],"decay":[46],"curve":[47,69],"for":[48,84,100,115],"unconditional":[50,66],"rate":[52,68],"function":[55],"sample":[58],"n,":[60],"and":[61,98],"fit":[62],"estimated":[65],"to":[70,91,135],"form.":[73],"result":[76,118],"Devijver,":[78],"do":[80],"twice,":[82],"once":[83],"k":[86],"nearest":[87,104],"neighbor":[88,105],"(kNN)":[89],"rule":[90,106],"provide":[92],"upper":[94],"bound":[95,114],"on":[96],"L*":[97,125],"again":[99],"Hellman's":[101],"(k;":[102],"k')":[103],"with":[107],"reject":[108],"option,":[109],"which":[110],"gives":[111],"lower":[113],"The":[117],"is":[119],"asymptotic":[121],"sample.":[130],"apply":[132],"our":[133],"estimator":[134],"two":[136],"examples,":[138],"obtaining":[139],"Bayes'":[140],"estimates.":[142]},"counts_by_year":[],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}