{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T16:11:37Z","timestamp":1762445497364,"version":"3.37.3"},"reference-count":23,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Turk Telekom Within the Framework of 5G and Beyond Joint Graduate Support Programme"},{"name":"Information and Communication Technologies Authority"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/lsp.2025.3537997","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T18:34:38Z","timestamp":1738607678000},"page":"816-820","source":"Crossref","is-referenced-by-count":1,"title":["Fitting Multiple Machine Learning Models With Performance Based Clustering"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-2796-4888","authenticated-orcid":false,"given":"Mehmet E.","family":"Lorasdagi","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Bilkent University, Ankara, T&#x00FC;rkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7050-2687","authenticated-orcid":false,"given":"Ahmet B.","family":"Koc","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Bilkent University, Ankara, T&#x00FC;rkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9144-5974","authenticated-orcid":false,"given":"Ali T.","family":"Koc","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Bilkent University, Ankara, T&#x00FC;rkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6488-3848","authenticated-orcid":false,"given":"Suleyman S.","family":"Kozat","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Bilkent University, Ankara, T&#x00FC;rkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"article-title":"Wind turbine scada dataset","year":"2018","author":"Erisen","key":"ref1"},{"year":"2018","key":"ref2","article-title":"Chicago crime"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2017.2757901"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2021.3111812"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3146136"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380214"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3216454"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_9"},{"article-title":"Deep temporal clustering : Fully unsupervised learning of time-domain features","year":"2018","author":"Madiraju","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9006561"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/79.543975"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2020.3016185"},{"volume-title":"Pattern Classification","year":"2000","author":"Duda","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2020.3005051"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2014.2299814"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729548"},{"key":"ref18","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-21506-8","volume-title":"Understanding Analysis","volume":"2","author":"Abbott","year":"2001"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s003570000022"},{"volume-title":"Deep Learning","year":"2016","author":"Goodfellow","key":"ref20"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2018.06.001"},{"article-title":"Regression datasets","year":"2023","author":"Torgo","key":"ref22"},{"article-title":"Daily climate time series data","year":"2020","author":"Rao","key":"ref23"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/97\/10802935\/10870195.pdf?arnumber=10870195","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:21:57Z","timestamp":1740122517000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10870195\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/lsp.2025.3537997","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"type":"print","value":"1070-9908"},{"type":"electronic","value":"1558-2361"}],"subject":[],"published":{"date-parts":[[2025]]}}}