{"id":"https://openalex.org/W6922325780","doi":"https://doi.org/10.1184/r1/23576451.v1","title":"Comparing Forecasters and Abstaining Classifiers","display_name":"Comparing Forecasters and Abstaining Classifiers","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W6922325780","doi":"https://doi.org/10.1184/r1/23576451.v1"},"language":"en","primary_location":{"id":"pmh:oai:figshare.com:article/23576451","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Choe, Yo Joong","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Choe, Yo Joong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38058961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.1703999936580658,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.1703999936580658,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.11670000106096268,"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":0.07490000128746033,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.8615000247955322},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5979999899864197},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5608000159263611},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5450000166893005},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.48649999499320984},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.3978999853134155}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.8615000247955322},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5979999899864197},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5608000159263611},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5450000166893005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.510699987411499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5062999725341797},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.48649999499320984},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4832000136375427},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3978999853134155},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3831999897956848},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2867000102996826},{"id":"https://openalex.org/C5465570","wikidata":"https://www.wikidata.org/wiki/Q5326898","display_name":"Early stopping","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C3020493868","wikidata":"https://www.wikidata.org/wiki/Q55631277","display_name":"Real world data","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C2983220686","wikidata":"https://www.wikidata.org/wiki/Q951437","display_name":"Interval data","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:figshare.com:article/23576451","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.1184/r1/23576451.v1","is_oa":true,"landing_page_url":"https://doi.org/10.1184/r1/23576451.v1","pdf_url":null,"source":{"id":"https://openalex.org/S7407050927","display_name":"KiltHub Repository","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/23576451","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"thesis":[1],"concerns":[2],"nonparametric":[3],"statistical":[4],"methods":[5],"for":[6,30,210,225,233],"comparing":[7,31,130],"black-box":[8,131],"predictors,":[9],"namely":[10],"sequential":[11],"forecasters":[12,33],"and":[13,27,98,129,161,218,221,229],"abstaining":[14,132],"classifiers.":[15,133],"In":[16,116],"the":[17,21,42,50,56,84,87,91,117,121,125,137,164,169,183,188,192,206,211,223,234,243],"first":[18],"part":[19,119],"of":[20,44,86,120,127,171,191],"thesis,":[22,122],"we":[23,123],"develop":[24,96],"anytime-valid":[25],"estimation":[26],"testing":[28,102],"approaches":[29],"probability":[32],"on":[34,83,90,142],"sequentially":[35],"occurring":[36],"events.":[37],"Our":[38,177],"main":[39],"contribution":[40],"is":[41,179],"development":[43],"confidence":[45,60],"sequences":[46],"(CS)":[47],"that":[48,106,144],"estimate":[49],"time-varying":[51],"average":[52],"score":[53],"difference":[54,244],"between":[55],"forecasters.":[57],"Unlike":[58],"classical":[59],"intervals,":[61],"CSs":[62,75,105],"can":[63],"be":[64],"continuously":[65],"monitored":[66],"over":[67],"time":[68],"while":[69],"retaining":[70],"their":[71],"coverage":[72],"guarantees.":[73],"The":[74,201,236],"also":[76,238],"do":[77],"not":[78,196],"require":[79],"any":[80,112],"distributional":[81],"assumptions":[82],"dynamics":[85],"outcomes":[88],"or":[89],"forecasting":[92],"models.":[93],"We":[94,156],"additionally":[95],"e-processes":[97],"p-processes,":[99],"which":[100,186],"are":[101,107,146],"counterparts":[103],"to":[104,139,163,199,241],"anytime-valid,":[108],"i.e.,":[109],"valid":[110],"at":[111],"data-dependent":[113],"stopping":[114],"times.":[115],"second":[118],"consider":[124],"problem":[126,166],"evaluating":[128],"Abstaining":[134],"classifiers":[135],"have":[136],"option":[138],"withhold":[140],"predictions":[141],"inputs":[143],"they":[145],"uncertain":[147],"about,":[148],"making":[149],"them":[150],"increasingly":[151],"popular":[152],"in":[153,245],"safety-critical":[154],"applications.":[155],"introduce":[157],"a":[158,172,226],"novel":[159],"approach":[160,178,237],"perspective":[162,204],"evaluation":[165,216],"by":[167],"treating":[168],"abstentions":[170],"classifier":[173,193],"as":[174],"missing":[175,202],"data.":[176],"centered":[180],"around":[181],"defining":[182],"counterfactual":[184,212,247],"score,":[185,213],"measures":[187],"expected":[189],"performance":[190],"had":[194],"it":[195],"been":[197],"allowed":[198],"abstain.":[200],"data":[203,217],"clarifies":[205],"precise":[207],"identifying":[208],"conditions":[209],"requiring":[214],"independent":[215],"stochastic":[219],"abstentions,":[220],"paves":[222],"way":[224],"nonparametrically":[227],"efficient":[228],"doubly":[230],"robust":[231],"estimator":[232],"score.":[235],"straightforwardly":[239],"extends":[240],"estimating":[242],"two":[246],"scores":[248],"under":[249],"distinct":[250],"abstention":[251],"mechanisms.":[252]},"counts_by_year":[],"updated_date":"2026-02-12T00:53:03.260389","created_date":"2025-10-10T00:00:00"}
