{"id":"https://openalex.org/W3115948762","doi":"https://doi.org/10.1007/s10618-020-00727-3","title":"The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances","display_name":"The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances","publication_year":2020,"publication_date":"2020-12-18","ids":{"openalex":"https://openalex.org/W3115948762","doi":"https://doi.org/10.1007/s10618-020-00727-3","mag":"3115948762","pmid":"https://pubmed.ncbi.nlm.nih.gov/33679210"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-020-00727-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-020-00727-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-020-00727-3.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"type":"review","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-020-00727-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018499833","display_name":"Alejandro Pasos Ruiz","orcid":"https://orcid.org/0000-0001-7129-821X"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Alejandro Pasos Ruiz","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084299179","display_name":"Michael Flynn","orcid":"https://orcid.org/0000-0002-6811-5395"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Michael Flynn","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081063163","display_name":"James Large","orcid":"https://orcid.org/0000-0002-2357-3798"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James Large","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077659042","display_name":"Matthew Middlehurst","orcid":"https://orcid.org/0000-0002-3293-8779"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Matthew Middlehurst","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052586692","display_name":"Anthony Bagnall","orcid":"https://orcid.org/0000-0003-2360-8994"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Anthony Bagnall","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018499833"],"corresponding_institution_ids":["https://openalex.org/I1118541"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":34.2378,"has_fulltext":true,"cited_by_count":440,"citation_normalized_percentile":{"value":0.99850163,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"35","issue":"2","first_page":"401","last_page":"449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9781000018119812,"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/T11309","display_name":"Music and Audio Processing","score":0.9674999713897705,"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/univariate","display_name":"Univariate","score":0.835471510887146},{"id":"https://openalex.org/keywords/bespoke","display_name":"Bespoke","score":0.7633039355278015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6427772045135498},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6394225358963013},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5484387278556824},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.5372732877731323},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5318149328231812},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5308889746665955},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5090755820274353},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.45433148741722107},{"id":"https://openalex.org/keywords/bioregion","display_name":"Bioregion","score":0.44235652685165405},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42127931118011475},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3214454650878906},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32077205181121826}],"concepts":[{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.835471510887146},{"id":"https://openalex.org/C44210515","wikidata":"https://www.wikidata.org/wiki/Q16968978","display_name":"Bespoke","level":2,"score":0.7633039355278015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6427772045135498},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6394225358963013},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5484387278556824},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.5372732877731323},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5318149328231812},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5308889746665955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5090755820274353},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.45433148741722107},{"id":"https://openalex.org/C2778371126","wikidata":"https://www.wikidata.org/wiki/Q2904233","display_name":"Bioregion","level":3,"score":0.44235652685165405},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42127931118011475},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3214454650878906},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32077205181121826},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C185933670","wikidata":"https://www.wikidata.org/wiki/Q52105","display_name":"Habitat","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/s10618-020-00727-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-020-00727-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-020-00727-3.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},{"id":"pmid:33679210","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33679210","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data mining and knowledge discovery","raw_type":null},{"id":"pmh:oai:eprints.soton.ac.uk:495341","is_oa":true,"landing_page_url":"http://doi.org/10.1007/s10618-020-00727-3>).","pdf_url":"https://eprints.soton.ac.uk/495341/1/s10618-020-00727-3.pdf","source":{"id":"https://openalex.org/S4306401019","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:ueaeprints.uea.ac.uk:77815","is_oa":true,"landing_page_url":null,"pdf_url":"https://ueaeprints.uea.ac.uk/id/eprint/77815/7/Ruiz2020_Article_TheGreatMultivariateTimeSeries.pdf","source":{"id":"https://openalex.org/S4306400384","display_name":"UEA Digital Repository (University of East Anglia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1118541","host_organization_name":"University of East Anglia","host_organization_lineage":["https://openalex.org/I1118541"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:pubmedcentral.nih.gov:7897627","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7897627","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Min Knowl Discov","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s10618-020-00727-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-020-00727-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-020-00727-3.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1934935867","display_name":null,"funder_award_id":"Engineering and Physical Sciences R","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3087056252","display_name":null,"funder_award_id":"EP/M015807/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G4333889053","display_name":"The Norwich Research Park Biosciences Doctoral Training Partnership","funder_award_id":"BB/M011216/1","funder_id":"https://openalex.org/F4320334629","funder_display_name":"Biotechnology and Biological Sciences Research Council"},{"id":"https://openalex.org/G4466388606","display_name":null,"funder_award_id":"NVIDIA","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G6739827899","display_name":"The Collective of Transform Ensembles (COTE) for Time Series Classification","funder_award_id":"EP/M015807/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320320274","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93"},{"id":"https://openalex.org/F4320332167","display_name":"Directorate for Biological Sciences","ror":"https://ror.org/001xhss06"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320334629","display_name":"Biotechnology and Biological Sciences Research Council","ror":"https://ror.org/00cwqg982"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3115948762.pdf","grobid_xml":"https://content.openalex.org/works/W3115948762.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W67158865","https://openalex.org/W789250018","https://openalex.org/W812433350","https://openalex.org/W1565746575","https://openalex.org/W1693343509","https://openalex.org/W1731081199","https://openalex.org/W1968354112","https://openalex.org/W1984674851","https://openalex.org/W2013366824","https://openalex.org/W2016944175","https://openalex.org/W2030863907","https://openalex.org/W2078932129","https://openalex.org/W2093534731","https://openalex.org/W2095858069","https://openalex.org/W2097117768","https://openalex.org/W2122189289","https://openalex.org/W2147780311","https://openalex.org/W2162800060","https://openalex.org/W2163605009","https://openalex.org/W2164274563","https://openalex.org/W2166547175","https://openalex.org/W2189007323","https://openalex.org/W2194775991","https://openalex.org/W2283896980","https://openalex.org/W2343110772","https://openalex.org/W2468738844","https://openalex.org/W2545993457","https://openalex.org/W2551393996","https://openalex.org/W2555077524","https://openalex.org/W2581867724","https://openalex.org/W2616619856","https://openalex.org/W2726969888","https://openalex.org/W2754051771","https://openalex.org/W2765753848","https://openalex.org/W2766453073","https://openalex.org/W2771712594","https://openalex.org/W2783323081","https://openalex.org/W2786161686","https://openalex.org/W2802183958","https://openalex.org/W2809338893","https://openalex.org/W2892035503","https://openalex.org/W2911964244","https://openalex.org/W2946507061","https://openalex.org/W2951544399","https://openalex.org/W2966392777","https://openalex.org/W2967988901","https://openalex.org/W2972808170","https://openalex.org/W2972810968","https://openalex.org/W2982438846","https://openalex.org/W2984797972","https://openalex.org/W2988244882","https://openalex.org/W2998010409","https://openalex.org/W3042807565","https://openalex.org/W3044508433","https://openalex.org/W3080921724","https://openalex.org/W3083891030","https://openalex.org/W3098918569","https://openalex.org/W4248337693","https://openalex.org/W4255601674","https://openalex.org/W4289360400","https://openalex.org/W4293477908"],"related_works":["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","https://openalex.org/W2912721996"],"abstract_inverted_index":{"Time":[0],"Series":[1],"Classification":[2],"(TSC)":[3],"involves":[4],"building":[5],"predictive":[6],"models":[7],"for":[8,80,109],"a":[9,21,57,61,81,106,116,178],"discrete":[10],"target":[11],"variable":[12],"from":[13],"ordered,":[14],"real":[15],"valued,":[16],"attributes.":[17],"Over":[18],"recent":[19],"years,":[20],"new":[22],"set":[23,118],"of":[24,39,115,119,135,145,162,204,215,237,255],"TSC":[25,73],"algorithms":[26,146,154,195],"have":[27,31],"been":[28,46,93,127],"developed":[29],"which":[30],"made":[32,143],"significant":[33,244],"improvement":[34,245],"over":[35,187],"the":[36,40,51,77,98,113,173,188,193,202,205,211,228,247,260],"previous":[37],"state":[38],"art.":[41],"The":[42,101,132],"main":[43],"focus":[44,129],"has":[45,56,84,92,104,126,142],"on":[47,130,156,201,246],"univariate":[48,99,110,179],"TSC,":[49,111],"i.e.":[50],"problem":[52],"where":[53,76,210],"each":[54],"case":[55,83],"single":[58,82],"series":[59,79],"and":[60,112,160,234],"class":[62],"label.":[63],"In":[64],"reality,":[65],"it":[66,186],"is":[67,183],"more":[68,225],"common":[69],"to":[70,95,176,181,184,196],"encounter":[71],"multivariate":[72,171,189],"(MTSC)":[74],"problems":[75,121,138,209],"time":[78,231,258],"multiple":[85],"dimensions.":[86,190],"Despite":[87],"this,":[88],"much":[89],"less":[90,128,257],"consideration":[91],"given":[94],"MTSC":[96,137,153,182,207],"than":[97,227,259],"case.":[100],"UCR":[102],"archive":[103,134,208,248],"provided":[105],"valuable":[107],"resource":[108],"lack":[114],"standard":[117],"test":[120],"may":[122],"explain":[123],"why":[124],"there":[125],"MTSC.":[131],"UEA":[133],"30":[136,206],"released":[139],"in":[140,250],"2018":[141],"comparison":[144],"easier.":[147],"We":[148,191,218],"review":[149],"recently":[150,239],"proposed":[151,240],"bespoke":[152,194],"based":[155],"deep":[157],"learning,":[158],"shapelets":[159],"bag":[161],"words":[163],"approaches.":[164],"If":[165],"an":[166,253],"algorithm":[167,233],"cannot":[168],"naturally":[169],"handle":[170],"data,":[172],"simplest":[174],"approach":[175],"adapt":[177],"classifier":[180],"ensemble":[185],"compare":[192],"these":[197,238],"dimension":[198],"independent":[199],"approaches":[200],"26":[203],"data":[212],"are":[213,223],"all":[214],"equal":[216],"length.":[217],"demonstrate":[219],"that":[220,235],"four":[221],"classifiers":[222],"significantly":[224],"accurate":[226],"benchmark":[229],"dynamic":[230],"warping":[232],"one":[236],"classifiers,":[241],"ROCKET,":[242],"achieves":[243],"datasets":[249],"at":[251],"least":[252],"order":[254],"magnitude":[256],"other":[261],"three.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":15},{"year":2025,"cited_by_count":84},{"year":2024,"cited_by_count":116},{"year":2023,"cited_by_count":120},{"year":2022,"cited_by_count":85},{"year":2021,"cited_by_count":20}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}