R: Dimensionality Reduction via Regression.

DRR-package {DRR} | R Documentation

## 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 gkraemer@bgc-jena.mpg.de

### 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

[Package DRR version 0.0.3 Index]