getCaretParamSet {mlr} | R Documentation |
Get tuning parameters from a learner of the caret R-package.
Description
Constructs a grid of tuning parameters from a learner of the caret
R-package. These values are then converted into a list of non-tunable
parameters (par.vals
) and a tunable
ParamHelpers::ParamSet (par.set
), which can be used by
tuneParams for tuning the learner. Numerical parameters will
either be specified by their lower and upper bounds or they will be
discretized into specific values.
Usage
getCaretParamSet(learner, length = 3L, task, discretize = TRUE)
Arguments
learner |
( |
length |
( |
task |
(Task) |
discretize |
( |
Value
(list(2)
). A list of parameters:
par.vals
contains a list of all constant tuning parameterspar.set
is a ParamHelpers::ParamSet, containing all the configurable tuning parameters
Examples
if (requireNamespace("caret") && requireNamespace("mlbench")) {
library(caret)
classifTask = makeClassifTask(data = iris, target = "Species")
# (1) classification (random forest) with discretized parameters
getCaretParamSet("rf", length = 9L, task = classifTask, discretize = TRUE)
# (2) regression (gradient boosting machine) without discretized parameters
library(mlbench)
data(BostonHousing)
regrTask = makeRegrTask(data = BostonHousing, target = "medv")
getCaretParamSet("gbm", length = 9L, task = regrTask, discretize = FALSE)
}