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Autor:
Hayes, Dustin, Kovalerchuk, Boris
This work uses visual knowledge discovery in parallel coordinates to advance methods of interpretable machine learning. The graphic data representation in parallel coordinates made the concepts of hypercubes and hyperblocks (HBs) simple to understand
Externí odkaz:
http://arxiv.org/abs/2305.18434
Autor:
Kovalerchuk, Boris, Hayes, Dustin
This paper contributes to interpretable machine learning via visual knowledge discovery in parallel coordinates. The concepts of hypercubes and hyper-blocks are used as easily understandable by end-users in the visual form in parallel coordinates. Th
Externí odkaz:
http://arxiv.org/abs/2106.07474
Autor:
Bisson, Kelsey M., Baetge, Nicholas, Kramer, Sasha J., Catlett, Dylan, Girling, Gad, McNair, Heather, Arrington, Eleanor, Hayes, Dustin, Jacobs, Celia, James, Anna, Closset, Ivia, Fischer, Alexis D., Wagner, Sasha, Reading, Mariah, Comstock, Jacqueline, Amiri, Sarah, Harvey, Elizabeth, Carlson, Craig, Gaube, Peter, Drushka, Kyla, Valentine, David L.
Publikováno v:
Oceanography, 2020 Mar 01. 33(1), 16-19.
Externí odkaz:
https://www.jstor.org/stable/26897831
