{"id":"https://openalex.org/W4401353384","doi":"https://doi.org/10.14778/3665844.3665863","title":"TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods","display_name":"TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods","publication_year":2024,"publication_date":"2024-05-01","ids":{"openalex":"https://openalex.org/W4401353384","doi":"https://doi.org/10.14778/3665844.3665863"},"language":"en","primary_location":{"id":"doi:10.14778/3665844.3665863","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3665844.3665863","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://vbn.aau.dk/ws/files/757799316/2403.20150v3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058572131","display_name":"Xiangfei Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangfei Qiu","raw_affiliation_strings":["East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111855573","display_name":"Jilin Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jilin Hu","raw_affiliation_strings":["East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102638299","display_name":"Lekui Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lekui Zhou","raw_affiliation_strings":["Huawei Cloud Algorithm Innovation Lab, China"],"affiliations":[{"raw_affiliation_string":"Huawei Cloud Algorithm Innovation Lab, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009377579","display_name":"Xingjian Wu","orcid":"https://orcid.org/0009-0007-1879-4653"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingjian Wu","raw_affiliation_strings":["East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059121729","display_name":"Junyang Du","orcid":"https://orcid.org/0000-0002-2837-2688"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyang Du","raw_affiliation_strings":["East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067787927","display_name":"B Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Buang Zhang","raw_affiliation_strings":["East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084021933","display_name":"Chenjuan Guo","orcid":"https://orcid.org/0000-0002-4516-4637"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenjuan Guo","raw_affiliation_strings":["East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101511862","display_name":"Aoying Zhou","orcid":"https://orcid.org/0000-0002-4665-7302"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aoying Zhou","raw_affiliation_strings":["East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029380368","display_name":"Christian S. Jensen","orcid":"https://orcid.org/0000-0002-9697-7670"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Christian S. Jensen","raw_affiliation_strings":["Aalborg University, Denmark"],"affiliations":[{"raw_affiliation_string":"Aalborg University, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003050907","display_name":"Zhenli Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenli Sheng","raw_affiliation_strings":["Huawei Cloud Algorithm, Innovation Lab, China"],"affiliations":[{"raw_affiliation_string":"Huawei Cloud Algorithm, Innovation Lab, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072309548","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0002-1658-1079"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["East China Normal, University, China"],"affiliations":[{"raw_affiliation_string":"East China Normal, University, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5058572131"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":34.6155,"has_fulltext":true,"cited_by_count":102,"citation_normalized_percentile":{"value":0.99909939,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"17","issue":"9","first_page":"2363","last_page":"2377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9976000189781189,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9909999966621399,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.7441574931144714},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7245262861251831},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5905186533927917},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5873482823371887},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5720794796943665},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.53462153673172},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5105918049812317},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49691274762153625},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4469166398048401},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.37472277879714966}],"concepts":[{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.7441574931144714},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7245262861251831},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5905186533927917},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5873482823371887},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5720794796943665},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.53462153673172},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5105918049812317},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49691274762153625},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4469166398048401},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.37472277879714966},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/3665844.3665863","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3665844.3665863","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire/98b9f964-d65f-437a-896f-98dc43d9b64d","is_oa":true,"landing_page_url":"https://vbn.aau.dk/da/publications/98b9f964-d65f-437a-896f-98dc43d9b64d","pdf_url":"https://vbn.aau.dk/ws/files/757799316/2403.20150v3.pdf","source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Qiu, X, Hu, J, Zhou, L, Wu, X, Du, J, Zhang, B, Guo, C, Zhou, A, Jensen, C S, Sheng, Z & Yang, B 2024, 'TFB : Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods', Proceedings of the VLDB Endowment, vol. 17, no. 9, 9, pp. 2363-2377. https://doi.org/10.14778/3665844.3665863","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire/98b9f964-d65f-437a-896f-98dc43d9b64d","is_oa":true,"landing_page_url":"https://vbn.aau.dk/da/publications/98b9f964-d65f-437a-896f-98dc43d9b64d","pdf_url":"https://vbn.aau.dk/ws/files/757799316/2403.20150v3.pdf","source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Qiu, X, Hu, J, Zhou, L, Wu, X, Du, J, Zhang, B, Guo, C, Zhou, A, Jensen, C S, Sheng, Z & Yang, B 2024, 'TFB : Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods', Proceedings of the VLDB Endowment, vol. 17, no. 9, 9, pp. 2363-2377. https://doi.org/10.14778/3665844.3665863","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401353384.pdf","grobid_xml":"https://content.openalex.org/works/W4401353384.grobid-xml"},"referenced_works_count":70,"referenced_works":["https://openalex.org/W317957491","https://openalex.org/W1973263126","https://openalex.org/W2084049265","https://openalex.org/W2116174583","https://openalex.org/W2151881411","https://openalex.org/W2257263437","https://openalex.org/W2525908418","https://openalex.org/W2604847698","https://openalex.org/W2607045400","https://openalex.org/W2743351235","https://openalex.org/W2754880706","https://openalex.org/W2785409760","https://openalex.org/W2808800115","https://openalex.org/W2893230400","https://openalex.org/W2967988901","https://openalex.org/W2980994438","https://openalex.org/W2996847713","https://openalex.org/W3004114474","https://openalex.org/W3011820231","https://openalex.org/W3037671731","https://openalex.org/W3042888527","https://openalex.org/W3092376471","https://openalex.org/W3105289605","https://openalex.org/W3111507638","https://openalex.org/W3123185352","https://openalex.org/W3123329971","https://openalex.org/W3156434410","https://openalex.org/W3173539742","https://openalex.org/W3173650575","https://openalex.org/W3174697924","https://openalex.org/W3175110359","https://openalex.org/W3175924508","https://openalex.org/W3177318507","https://openalex.org/W3187633063","https://openalex.org/W3201789021","https://openalex.org/W3202971245","https://openalex.org/W3204589526","https://openalex.org/W3212890323","https://openalex.org/W3217545443","https://openalex.org/W4221156048","https://openalex.org/W4224324885","https://openalex.org/W4225862894","https://openalex.org/W4230410911","https://openalex.org/W4246587917","https://openalex.org/W4280626475","https://openalex.org/W4285029217","https://openalex.org/W4286908664","https://openalex.org/W4289533840","https://openalex.org/W4289533938","https://openalex.org/W4290652269","https://openalex.org/W4306884390","https://openalex.org/W4307492541","https://openalex.org/W4309651345","https://openalex.org/W4315588609","https://openalex.org/W4318775883","https://openalex.org/W4320352504","https://openalex.org/W4323644197","https://openalex.org/W4380433143","https://openalex.org/W4382203079","https://openalex.org/W4382239356","https://openalex.org/W4383605061","https://openalex.org/W4386768620","https://openalex.org/W4386768622","https://openalex.org/W4388620469","https://openalex.org/W4390285500","https://openalex.org/W4392453192","https://openalex.org/W4392453352","https://openalex.org/W4403600951","https://openalex.org/W6793979478","https://openalex.org/W6907814131"],"related_works":["https://openalex.org/W4399363378","https://openalex.org/W1828158523","https://openalex.org/W2049578243","https://openalex.org/W2000145235","https://openalex.org/W2122079181","https://openalex.org/W1985848810","https://openalex.org/W2889939530","https://openalex.org/W3121881699","https://openalex.org/W2748838164","https://openalex.org/W2066015000"],"abstract_inverted_index":{"Time":[0,63,221,234],"series":[1,133,230],"are":[2,28,141,260],"generated":[3],"in":[4,47],"diverse":[5,152],"domains":[6,112],"such":[7,44],"as":[8],"economic,":[9,120],"traffic,":[10,114],"health,":[11,124],"and":[12,42,50,80,95,98,125,161,165,174,195,203,231,266,270],"energy,":[13,116],"where":[14],"forecasting":[15,26,250],"of":[16,86,154,171,182,189,218,248,278],"future":[17],"values":[18],"has":[19],"numerous":[20],"important":[21],"applications.":[22],"Not":[23],"surprisingly,":[24],"many":[25],"methods":[27,45,191,225,238],"being":[29],"proposed.":[30],"To":[31,53,101,143,185],"ensure":[32,136,177],"progress,":[33],"it":[34],"is":[35],"essential":[36],"to":[37,40,76,135,176,213,254],"be":[38],"able":[39],"study":[41],"compare":[43],"empirically":[46],"a":[48,131,151,169,178,201,215,245],"comprehensive":[49,180],"reliable":[51],"manner.":[52],"achieve":[54,102],"this,":[55],"we":[56,106,149,166,210],"propose":[57],"TFB,":[58],"an":[59],"automated":[60],"benchmark":[61,194],"for":[62,263],"Series":[64,222,235],"Forecasting":[65,223,236],"(TSF)":[66],"methods.":[67,184,282],"TFB":[68,199,212,269],"advances":[69],"the":[70,117,126,138,187,193,249,257],"state-of-the-art":[71],"by":[72],"addressing":[73],"shortcomings":[74],"related":[75],"datasets,":[77],"comparison":[78],"methods,":[79,94,148,155,164,251],"evaluation":[81,172,217,272],"pipelines:":[82],"1)":[83],"insufficient":[84],"coverage":[85],"data":[87],"domains,":[88],"2)":[89],"stereotype":[90],"bias":[91],"against":[92,146],"traditional":[93],"3)":[96],"inconsistent":[97],"inflexible":[99],"pipelines.":[100],"better":[103,255],"domain":[104],"coverage,":[105],"include":[107,150],"datasets":[108,140,265],"from":[109],"10":[110],"different":[111,183,190],":":[113],"electricity,":[115],"environment,":[118],"nature,":[119],"stock":[121],"markets,":[122],"banking,":[123],"web.":[127],"We":[128],"also":[129,167],"provide":[130,273],"time":[132,229],"characterization":[134],"that":[137,206,259],"selected":[139],"comprehensive.":[142],"remove":[144],"biases":[145],"some":[147],"range":[153],"including":[156],"statistical":[157],"learning,":[158,160],"machine":[159],"deep":[162],"learning":[163],"support":[168,186],"variety":[170],"strategies":[173],"metrics":[175],"more":[179],"evaluations":[181],"integration":[188],"into":[192],"enable":[196],"fair":[197],"comparisons,":[198],"features":[200],"flexible":[202],"scalable":[204],"pipeline":[205],"eliminates":[207],"biases.":[208],"Next,":[209],"employ":[211],"perform":[214],"thorough":[216],"21":[219],"Univariate":[220],"(UTSF)":[224],"on":[226,239],"8,068":[227],"univariate":[228],"14":[232],"Multivariate":[233],"(MTSF)":[237],"25":[240],"datasets.":[241],"The":[242],"results":[243],"offer":[244],"deeper":[246],"understanding":[247],"allowing":[252],"us":[253],"select":[256],"ones":[258],"most":[261],"suitable":[262],"particular":[264],"settings.":[267],"Overall,":[268],"this":[271],"researchers":[274],"with":[275],"improved":[276],"means":[277],"designing":[279],"new":[280],"TSF":[281]},"counts_by_year":[{"year":2026,"cited_by_count":21},{"year":2025,"cited_by_count":70},{"year":2024,"cited_by_count":11}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
