CVP_RIDGE {ADMMsigma} | R Documentation |
Parallel implementation of cross validation for RIDGEsigma.
CVP_RIDGE(X = NULL, lam = 10^seq(-2, 2, 0.1), K = 5, cores = 1,
trace = c("none", "progress", "print"))
X |
nxp data matrix. Each row corresponds to a single observation and each column contains n observations of a single feature/variable. |
lam |
positive tuning parameters for ridge penalty. If a vector of parameters is provided, they should be in increasing order. Defaults to grid of values |
K |
specify the number of folds for cross validation. |
cores |
option to run CV in parallel. Defaults to |
trace |
option to display progress of CV. Choose one of |
returns list of returns which includes:
lam |
optimal tuning parameter. |
min.error |
minimum average cross validation error for optimal parameters. |
avg.error |
average cross validation error across all folds. |
cv.error |
cross validation errors (negative validation likelihood). |