Description Usage Arguments Value Examples
This function plots the cross validation error as a function of the tuning parameters.
For penalties with 2 tuning parameters, a heat map will be plotted via the image()
function
1 |
mp_cv |
A fitted 'mp_cv' class object returned by |
col.regions |
color scale. See |
key.lab |
label for colorkey |
... |
arguments to be passed to |
Nothing
1 2 3 4 5 6 7 8 9 10 11 | set.seed(123)
sim_dat = simulated_dataset(n = 200, problem = "meta-analysis")
Xlist = sim_dat$Xlist; Ylist = sim_dat$Ylist; Trtlist = sim_dat$Trtlist
# fit different rules with lasso penalty for this meta-analysis problem
mp_cvmod_diff = mpersonalized_cv(problem = "meta-analysis",
Xlist = Xlist, Ylist = Ylist, Trtlist = Trtlist,
penalty = "lasso", single_rule = FALSE)
plots = plotCVE(mp_cvmod_diff)
set.seed(NULL)
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