乐胖代购免代理版

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$$\\lambda _{\\gamma }$$<\/jats:tex-math>\n \n \u03bb<\/mml:mi>\n \u03b3<\/mml:mi>\n <\/mml:msub>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> with parameter

$$\\gamma $$<\/jats:tex-math>\n \u03b3<\/mml:mi>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula>. We show that higher values of

$$\\gamma $$<\/jats:tex-math>\n \u03b3<\/mml:mi>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> place greater weight on larger pairwise differences, while lower values place greater weight on smaller pairwise differences. We\u00a0demonstrate that training

$$\\gamma $$<\/jats:tex-math>\n \u03b3<\/mml:mi>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> significantly improves the accuracy of both the

$${ DTW }$$<\/jats:tex-math>\n \n DTW<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula> nearest neighbor and Proximity Forest classifiers.\n<\/jats:p>","DOI":"10.1007\/s10618-023-00926-8","type":"journal-article","created":{"date-parts":[[2023,4,16]],"date-time":"2023-04-16T13:01:51Z","timestamp":1681650111000},"page":"2024-2045","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Parameterizing the cost function of dynamic time warping with application to time series classification"],"prefix":"10.1007","volume":"37","author":[{"given":"Matthieu","family":"Herrmann","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0001-8377-3241","authenticated-orcid":false,"given":"Chang Wei","family":"Tan","sequence":"additional","affiliation":[]},{"given":"Geoffrey I.","family":"Webb","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,16]]},"reference":[{"issue":"3","key":"926_CR1","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1007\/s10618-021-00740-0","volume":"35","author":"S Alaee","year":"2021","unstructured":"Alaee S, Mercer R, Kamgar K, Keogh E (2021) Time series motifs discovery under DTW allows more robust discovery of conserved structure. 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