plot.cv.kerndwd {kerndwd} | R Documentation |
Plot cross-validation error curves with the upper and lower standard deviations versus log lambda
values.
## S3 method for class 'cv.kerndwd' plot(x, sign.lambda, ...)
x |
A fitted |
sign.lambda |
Against |
... |
Other graphical parameters being passed to |
This function plots the cross-validation error curves. This function is modified based on the plot.cv
function of the glmnet
package.
Boxiang Wang and Hui Zou
Maintainer: Boxiang Wang boxiang@umn.edu
Wang, B. and Zou, H. (2018)
“Another Look at Distance Weighted Discrimination,"
Journal of Royal Statistical Society, Series B, 80(1), 177–198.
https://rss.onlinelibrary.wiley.com/doi/10.1111/rssb.12244
Friedman, J., Hastie, T., and Tibshirani, R. (2010), "Regularization paths for generalized
linear models via coordinate descent," Journal of Statistical Software, 33(1), 1–22.
http://www.jstatsoft.org/v33/i01/paper
set.seed(1) data(BUPA) BUPA$X = scale(BUPA$X, center=TRUE, scale=TRUE) lambda = 10^(seq(-3, 3, length.out=10)) kern = rbfdot(sigma=sigest(BUPA$X)) m.cv = cv.kerndwd(BUPA$X, BUPA$y, kern, qval=1, lambda=lambda, eps=1e-5, maxit=1e5) m.cv