Impact of cohort type and number of classes on algorithms.

<p>Algorithm accuracies were compared using Nemenyi tests in R package <i>mlr3benchmark</i>. Algorithms with similar accuracies are shown by the black bars in (A) and (C). (A) Average rank of the algorithms across all datasets is shown by the number of classes. (B) Average ranks fo...

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Bibliographic Details
Main Author:	Arshiya Mariam (10190281) (author)
Other Authors:	Hamed Javidi (19852442) (author), Emily C. Zabor (2831951) (author), Ran Zhao (337603) (author), Tomas Radivoyevitch (5431) (author), Daniel M. Rotroff (1329336) (author)
Published:	2024
Subjects:	Biochemistry Medicine Biotechnology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified sequence alignment tasks dynamic time warping derive meaningful insights consistently high bmi adjusted rand index applied 30 state shown immense promise robust algorithms tested longitudinal clinical measurements div >< p 93 – 6 highest accuracies across missingness impacted accuracies clinical measurements highest ari similar accuracies world settings unsupervised clustering trajectory shapes timeseries compiled systematic evaluation signal processing regular timeseries prior literature nemenyi tests median ari magnitude compared identify patterns greatest risk gaining insight fourteen partitional ci </ bound variants blood pressure ari ). algorithm identified accuracy using >: 3 70 ). 426 ). 30 methods 12 ).
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Impact of cohort type and number of classes on algorithms.

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