eyedata


Gene expression data (20 genes for 120 samples) from the microarray experiments of mammalianeye tissue samples of Scheetz et al. (2006).


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.

Xingguo Li

camel

Calibrated Machine Learning

eyedata function

The format is a list containing conatins a matrix and a vector.
  1. x - an 120 by 200 matrix, which represents the data of 120 rats with 200 gene probes.
  2. y - a 120-dimensional vector of, which represents the expression level of TRIM32 gene.

eyedata: Gene expression data for Bardet-Biedl syndrome from Scheetz et al. (2006)

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