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. 2022 Jun 3;13:887643. doi: 10.3389/fgene.2022.887643

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Copyright © 2022 Montesinos López, Mosqueda González, Palafox González, Montesinos López and Crossa.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Time in hours for implementing two sparse kernels (Arc_cosine_1 and Gaussian) with the maize data set as a function of the proportion of the compression level (0.5, 0.4, 0.3, 0.2, 0.1 and 0), which corresponds to using only the following proportions: 0.5, 0.6, 0.7, 0.8, 0.9 and 1 of the original lines (LinesProportion) for computing the sparse kernels since level of compression = 1 minus proportion of lines used to compute the sparse kernel. (A) corresponds to M4 and Arc_cosine_1 sparse kernel. (B) corresponds to M5 Arc_cosine_1 sparse kernel. (C) corresponds to M4 and Gaussian sparse kernel. (D) corresponds to M5 Gaussian sparse kernel. M4 denotes the random forest model and M5 denotes the Bayesian regression model.