{"id":"https://openalex.org/W7170858409","doi":"https://doi.org/10.1007/s10115-026-02845-8","title":"Adaptive approaches towards fully incremental prediction interval for data stream regression","display_name":"Adaptive approaches towards fully incremental prediction interval for data stream regression","publication_year":2026,"publication_date":"2026-07-24","ids":{"openalex":"https://openalex.org/W7170858409","doi":"https://doi.org/10.1007/s10115-026-02845-8"},"language":"en","primary_location":{"id":"doi:10.1007/s10115-026-02845-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-026-02845-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-026-02845-8.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"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":"Knowledge and Information Systems","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/s10115-026-02845-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012583633","display_name":"Yibin Sun","orcid":"https://orcid.org/0000-0002-8325-1889"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Yibin Sun","raw_affiliation_strings":["School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143600979","display_name":"Bernhard Pfahringer","orcid":null},"institutions":[{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Bernhard Pfahringer","raw_affiliation_strings":["AI Institute, The University of Waikato, Hamilton, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Institute, The University of Waikato, Hamilton, New Zealand","institution_ids":["https://openalex.org/I52179390"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071380196","display_name":"Heitor Murilo Gomes","orcid":"https://orcid.org/0000-0002-5276-637X"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Heitor Murilo Gomes","raw_affiliation_strings":["School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080970505","display_name":"Albert Bifet","orcid":"https://orcid.org/0000-0002-8339-7773"},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]},{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["FR","NZ"],"is_corresponding":false,"raw_author_name":"Albert Bifet","raw_affiliation_strings":["AI Institute, The University of Waikato, Hamilton, New Zealand","LTCI, T\u00e9l\u00e9com Paris, IP Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Institute, The University of Waikato, Hamilton, New Zealand","institution_ids":["https://openalex.org/I52179390"]},{"raw_affiliation_string":"LTCI, T\u00e9l\u00e9com Paris, IP Paris, France","institution_ids":["https://openalex.org/I12356871","https://openalex.org/I4210165912"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012583633"],"corresponding_institution_ids":["https://openalex.org/I41156924"],"apc_list":{"value":2890,"currency":"USD","value_usd":2890},"apc_paid":{"value":2890,"currency":"USD","value_usd":2890},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.92715436,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":"68","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9883999824523926,"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":0.9883999824523926,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.0007999999797903001,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/interval","display_name":"Interval (graph theory)","score":0.6180999875068665},{"id":"https://openalex.org/keywords/prediction-interval","display_name":"Prediction interval","score":0.6100999712944031},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5221999883651733},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5174000263214111},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.49869999289512634},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.47049999237060547},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4268999993801117},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.41850000619888306}],"concepts":[{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.6180999875068665},{"id":"https://openalex.org/C103402496","wikidata":"https://www.wikidata.org/wiki/Q1106171","display_name":"Prediction interval","level":2,"score":0.6100999712944031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.535099983215332},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5321000218391418},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5221999883651733},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5174000263214111},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.47049999237060547},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4268999993801117},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.41850000619888306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3815000057220459},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.3720000088214874},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36340001225471497},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3093000054359436},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2924000024795532},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C205167067","wikidata":"https://www.wikidata.org/wiki/Q3300636","display_name":"Interval estimation","level":3,"score":0.2863999903202057},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C191252586","wikidata":"https://www.wikidata.org/wiki/Q1671453","display_name":"Interval arithmetic","level":3,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10115-026-02845-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-026-02845-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-026-02845-8.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"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":"Knowledge and Information Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10115-026-02845-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-026-02845-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-026-02845-8.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"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":"Knowledge and Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1076533817","display_name":null,"funder_award_id":"VUW2213","funder_id":"https://openalex.org/F4320335369","funder_display_name":"Marsden Fund"}],"funders":[{"id":"https://openalex.org/F4320335369","display_name":"Marsden Fund","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7170858409.pdf","grobid_xml":"https://content.openalex.org/works/W7170858409.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1452761747","https://openalex.org/W1534133012","https://openalex.org/W1560021816","https://openalex.org/W2006398000","https://openalex.org/W2010657328","https://openalex.org/W2011006316","https://openalex.org/W2023320048","https://openalex.org/W2043526380","https://openalex.org/W2048934352","https://openalex.org/W2055336003","https://openalex.org/W2055992413","https://openalex.org/W2074911163","https://openalex.org/W2099302642","https://openalex.org/W2126105956","https://openalex.org/W2132477882","https://openalex.org/W2134125037","https://openalex.org/W2143991132","https://openalex.org/W2521871869","https://openalex.org/W2528991849","https://openalex.org/W2626498001","https://openalex.org/W2774185825","https://openalex.org/W2807637204","https://openalex.org/W2884165914","https://openalex.org/W2888572760","https://openalex.org/W2946625243","https://openalex.org/W2963798770","https://openalex.org/W2964368240","https://openalex.org/W2991693423","https://openalex.org/W2996259305","https://openalex.org/W2999648422","https://openalex.org/W3090724444","https://openalex.org/W3095491482","https://openalex.org/W3126856044","https://openalex.org/W3204245177","https://openalex.org/W4242289937","https://openalex.org/W4249736682","https://openalex.org/W4291274535","https://openalex.org/W4298352105","https://openalex.org/W4395066773","https://openalex.org/W6926136718","https://openalex.org/W6944863912","https://openalex.org/W6964248249","https://openalex.org/W7133194121","https://openalex.org/W7133239795"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Prediction":[1,66],"intervals":[2],"(PIs)":[3],"are":[4],"a":[5,44,86,118],"practical":[6],"tool":[7],"for":[8,23],"uncertainty":[9],"quantification":[10],"in":[11],"regression,":[12],"but":[13],"comparatively":[14],"little":[15],"work":[16],"has":[17],"addressed":[18],"fully":[19,87],"incremental":[20,88],"PI":[21,53],"generation":[22],"data":[24,29],"streams.":[25],"In":[26],"streaming":[27],"settings,":[28],"arrive":[30],"continuously,":[31],"each":[32],"instance":[33],"is":[34],"typically":[35],"processed":[36],"once,":[37],"and":[38,55,92,96,113,122,150],"concept":[39],"drift":[40],"can":[41,129],"quickly":[42],"invalidate":[43],"previously":[45],"well-calibrated":[46],"interval.":[47],"These":[48],"properties":[49],"make":[50],"many":[51],"batch":[52],"methods":[54],"window-based":[56],"adaptations":[57],"difficult":[58],"to":[59,78,134],"apply":[60],"efficiently.":[61],"This":[62],"paper":[63],"studies":[64],"Adaptive":[65],"Interval":[67],"(AdaPI),":[68],"an":[69,105],"online":[70],"post-calibration":[71],"framework":[72,84],"that":[73,108,127],"adjusts":[74],"interval":[75,114,142],"width":[76],"according":[77],"observed":[79],"coverage.":[80],"We":[81,102],"instantiate":[82],"the":[83,135,145,154,159,165],"with":[85],"variant":[89,156],"of":[90,120],"Mean":[91],"Variance":[93],"Estimation":[94],"(MVE)":[95],"investigate":[97],"three":[98,166],"adaptive":[99,167],"scaling":[100],"functions.":[101],"also":[103],"adopt":[104],"evaluation":[106],"perspective":[107],"jointly":[109],"considers":[110],"coverage":[111,132],"accuracy":[112],"width.":[115],"Experiments":[116],"on":[117],"collection":[119],"real-world":[121],"synthetic":[123],"regression":[124],"streams":[125],"show":[126],"AdaPI":[128],"often":[130],"move":[131],"closer":[133],"desired":[136],"confidence":[137,148],"level":[138],"while":[139],"maintaining":[140],"competitive":[141],"width;":[143],"under":[144],"default":[146],"95%":[147],"setting":[149],"coverage-heavy":[151],"CING":[152],"weighting,":[153],"linear":[155],"frequently":[157],"gives":[158],"strongest":[160],"empirical":[161],"coverage\u2013width":[162],"trade-off":[163],"among":[164],"strategies.":[168]},"counts_by_year":[],"updated_date":"2026-07-26T05:49:09.470579","created_date":"2026-07-25T00:00:00"}