MLExperimentsBase | R Documentation |
R6 Class on which the experiment classes are built on
R6 Class on which the experiment classes are built on
mlexperiments::MLBase
-> MLExperimentsBase
learner_args
A list containing the parameter settings of the learner algorithm.
learner
An initialized learner object that inherits from class
"MLLearnerBase"
.
new()
Create a new MLExperimentsBase
object.
MLExperimentsBase$new(learner, seed, ncores = -1L)
learner
An initialized learner object that inherits from class
"MLLearnerBase"
.
seed
An integer. Needs to be set for reproducibility purposes.
ncores
An integer to specify the number of cores used for
parallelization (default: -1L
).
A new MLExperimentsBase
R6 object.
set_data()
Set the data for the experiment.
MLExperimentsBase$set_data(x, y, cat_vars = NULL)
x
A matrix with the training data.
y
A vector with the target.
cat_vars
A character vector with the column names of variables that should be treated as categorical features (if applicable / supported by the respective algorithm).
The function has no return value. It internally performs quality checks on the provided data and, if passed, defines private fields of the R6 class.
clone()
The objects of this class are cloneable with this method.
MLExperimentsBase$clone(deep = FALSE)
deep
Whether to make a deep clone.
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