DRR-package: Dimensionality Reduction via Regression.

In DRR: Dimensionality Reduction via Regression

Description

DRR implements the Dimensionality Reduction via Regression using Kernel Ridge Regression. It also adds a faster implementation of Kernel Ridge regression that can be used with the CVST package.

Details

Funding provided by the Department for Biogeochemical Integration, Empirical Inference of the Earth System Group, at the Max Plack Institute for Biogeochemistry, Jena.

Author(s)

Maintainer: Guido Kraemer [e-mail]

References

Laparra, V., Malo, J., Camps-Valls, G., 2015. Dimensionality Reduction via Regression in Hyperspectral Imagery. IEEE Journal of Selected Topics in Signal Processing 9, 1026-1036. doi:10.1109/JSTSP.2015.2417833 Zhang, Y., Duchi, J.C., Wainwright, M.J., 2013. Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates. arXiv:1305.5029 [cs, math, stat].

See Also

Useful links:

• https://github.com/gdkrmr/DRR

• Report bugs at https://github.com/gdkrmr/DRR/issues

DRR documentation built on Feb. 12, 2020, 5:59 p.m.