Usage
tune.control(random = FALSE, nrepeat = 1, repeat.aggregate = min,
sampling = c("cross", "fix", "bootstrap"), sampling.aggregate = mean,
sampling.dispersion = sd,
cross = 10, fix = 2/3, nboot = 10, boot.size = 9/10, best.model = TRUE,
performances = TRUE)Arguments
random
if an integer value is specified, random
parameter vectors are drawn from the parameter space.
nrepeat
specifies how often training shall be repeated.
repeat.aggregate
function for aggregating the repeated training results.
sampling
sampling scheme. If sampling = "cross", a
cross-times cross validation is performed. If sampling
= "boot", nboot training sets of size boot.size (part)
are sampled (with replac
sampling.aggregate,sampling.dispersion
functions for aggregating the training
results on the generated training samples (default: mean and
standard deviation).
cross
number of partitions for cross-validation.
fix
part of the data used for training in fixed sampling.
nboot
number of bootstrap replications.
boot.size
size of the bootstrap samples.
best.model
if TRUE, the best model is trained and
returned (the best parameter set is used for
training on the complete training set).
performances
if TRUE, the performance results for all
parameter combinations are returned.