{"id":"https://openalex.org/W4200027143","doi":"https://doi.org/10.1007/s10994-021-06084-6","title":"Maintaining AUC and H-measure over time","display_name":"Maintaining AUC and H-measure over time","publication_year":2021,"publication_date":"2021-12-14","ids":{"openalex":"https://openalex.org/W4200027143","doi":"https://doi.org/10.1007/s10994-021-06084-6"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-021-06084-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-021-06084-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-021-06084-6.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-021-06084-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067444605","display_name":"Nikolaj Tatti","orcid":"https://orcid.org/0000-0002-2087-5360"},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]},{"id":"https://openalex.org/I32943570","display_name":"Helsinki Institute for Information Technology","ror":"https://ror.org/05kph4940","country_code":"FI","type":"facility","lineage":["https://openalex.org/I133731052","https://openalex.org/I32943570","https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Nikolaj Tatti","raw_affiliation_strings":["HIIT, University of Helsinki, Helsinki, Finland"],"raw_orcid":"https://orcid.org/0000-0002-2087-5360","affiliations":[{"raw_affiliation_string":"HIIT, University of Helsinki, Helsinki, Finland","institution_ids":["https://openalex.org/I133731052","https://openalex.org/I32943570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067444605"],"corresponding_institution_ids":["https://openalex.org/I133731052","https://openalex.org/I32943570"],"apc_list":{"value":3290,"currency":"USD","value_usd":3290},"apc_paid":{"value":3290,"currency":"USD","value_usd":3290},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18692056,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"111","issue":"8","first_page":"2839","last_page":"2862"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","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/T12761","display_name":"Data Stream Mining Techniques","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"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":0.9972000122070312,"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/algorithm","display_name":"Algorithm","score":0.5900206565856934},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5413801670074463},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5246223211288452},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44129252433776855},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41655465960502625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32171571254730225}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5900206565856934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5413801670074463},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5246223211288452},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44129252433776855},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41655465960502625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32171571254730225}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10994-021-06084-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-021-06084-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-021-06084-6.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},{"id":"pmh:oai:helda.helsinki.fi:10138/347235","is_oa":true,"landing_page_url":"http://hdl.handle.net/10138/347235","pdf_url":null,"source":{"id":"https://openalex.org/S4210213322","display_name":"Ty\u00f6v\u00e4entutkimus Vuosikirja","issn_l":"0784-1272","issn":["0784-1272","1459-7780"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1007/s10994-021-06084-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-021-06084-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-021-06084-6.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310086","display_name":"Helsingin Yliopisto","ror":"https://ror.org/040af2s02"},{"id":"https://openalex.org/F4320310467","display_name":"Helsingin ja Uudenmaan Sairaanhoitopiiri","ror":"https://ror.org/020cpqb94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200027143.pdf","grobid_xml":"https://content.openalex.org/works/W4200027143.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1499467920","https://openalex.org/W1537430301","https://openalex.org/W1972978214","https://openalex.org/W2026166434","https://openalex.org/W2073256825","https://openalex.org/W2083905053","https://openalex.org/W2096606628","https://openalex.org/W2099419573","https://openalex.org/W2102387656","https://openalex.org/W2108004390","https://openalex.org/W2111700528","https://openalex.org/W2115650093","https://openalex.org/W2132445073","https://openalex.org/W2137959503","https://openalex.org/W2145139979","https://openalex.org/W2158917374","https://openalex.org/W2165880761","https://openalex.org/W2577513693","https://openalex.org/W2909210587"],"related_works":["https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W2961085424","https://openalex.org/W3200179079","https://openalex.org/W4249229055","https://openalex.org/W2556319748","https://openalex.org/W2891961174","https://openalex.org/W2512018286","https://openalex.org/W4310989423","https://openalex.org/W3158264953"],"abstract_inverted_index":{"Abstract":[0],"Measuring":[1],"the":[2,22,36,45,57,81,108,121,129,180,184,199,207,216,224,240,258,267,302],"performance":[3,58],"of":[4,17,59,89,132,198,223],"a":[5,8,25,42,60,113,133,187,195,204,220],"classifier":[6,37,61],"is":[7,38,54,104,186],"vital":[9],"task":[10],"in":[11,29,92,112,136,156,172,243,269],"machine":[12],"learning.":[13],"The":[14,75],"running":[15,46],"time":[16,47],"an":[18,30,175],"algorithm":[19,77],"that":[20,124,212,233,295],"computes":[21],"measure":[23,177,185],"plays":[24],"very":[26],"small":[27],"role":[28],"offline":[31],"setting,":[32],"for":[33,71],"example,":[34],"when":[35],"being":[39],"developed":[40],"by":[41,106,203],"researcher.":[43],"However,":[44],"becomes":[48],"more":[49],"crucial":[50],"if":[51,257],"our":[52,296],"goal":[53],"to":[55,127,153,193],"monitor":[56],"over":[62,206],"time.":[63,102,146,166,291],"In":[64,117,147],"this":[65],"paper":[66],"we":[67,119,150,191,213,237,264],"study":[68],"three":[69],"algorithms":[70,170],"maintaining":[72,107,173],"two":[73,169],"measures.":[74],"first":[76,190],"maintains":[78],"area":[79],"under":[80,85,234],"ROC":[82,130,181,200],"curve":[83],"(AUC)":[84],"addition":[86],"and":[87,256],"deletion":[88],"data":[90,109,134],"points":[91,110],"$$\\mathcal":[93,137,157,244,270],"{O}":[94,138,158,245,271],"\\mathopen":[95,139,159,246,272],"{}\\left(":[96,140,160,247,273],"\\log":[97,141,161,248],"n\\right)$$":[98,142,162,250,279],"O":[99,143,163,251,280],"log":[100,144,164,252,282,289],"n":[101,145,165,254,275,283,290],"This":[103],"done":[105],"sorted":[111],"self-balanced":[114],"search":[115,122],"tree.":[116],"addition,":[118],"augment":[120],"tree":[123],"allows":[125],"us":[126],"query":[128],"coordinates":[131],"point":[135],"doing":[148],"so":[149],"are":[151,260,298],"able":[152],"maintain":[154,215],"AUC":[155],"Our":[167],"next":[168],"involve":[171],"H-measure,":[174],"alternative":[176],"based":[178],"on":[179],"curve.":[182],"Computing":[183],"two-step":[188],"process:":[189],"need":[192],"compute":[194,239],"convex":[196,208,217,226],"hull":[197,218,227],"curve,":[201],"followed":[202],"sum":[205],"hull.":[209],"We":[210,230,292],"demonstrate":[211],"can":[214,238,265],"using":[219],"minor":[221],"modification":[222],"classic":[225],"maintenance":[228],"algorithm.":[229],"then":[231,263],"show":[232,293],"certain":[235],"conditions,":[236],"H-measure":[241,268],"exactly":[242],"^2":[249],"2":[253],"time,":[255],"conditions":[259],"not":[261],"met,":[262],"estimate":[266],"(\\log":[274],"+":[276,284],"\\epsilon":[277],"^{-1})\\log":[278],"(":[281],"\u03f5":[285],"-":[286],"1":[287],")":[288],"empirically":[294],"methods":[297],"significantly":[299],"faster":[300],"than":[301],"baselines.":[303]},"counts_by_year":[],"updated_date":"2026-08-23T07:36:19.812096","created_date":"2025-10-10T00:00:00"}