camel: Calibrated Machine Learning
The package "camel" provides the implementation of a family of high-dimensional calibrated machine learning tools, including (1) LAD, SQRT Lasso and Calibrated Dantzig Selector for estimating sparse linear models; (2) Calibrated Multivariate Regression for estimating sparse multivariate linear models; (3) Tiger, Calibrated Clime for estimating sparse Gaussian graphical models. We adopt the combination of the dual smoothing and monotone fast iterative soft-thresholding algorithm (MFISTA). The computation is memory-optimized using the sparse matrix output, and accelerated by the path following and active set tricks.
| Version: |
0.2.0 |
| Depends: |
R (≥ 2.15.0), lattice, igraph, MASS, Matrix |
| Published: |
2013-09-09 |
| Author: |
Xingguo Li, Tuo Zhao, and Han Liu |
| Maintainer: |
Xingguo Li <xingguo.leo at gmail.com> |
| License: |
GPL-2 |
| NeedsCompilation: |
yes |
| CRAN checks: |
camel results |
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