MLExperimentsBase {mlexperiments}

R6 Class on which the experiment classes are built on

Description

R6 Class on which the experiment classes are built on

R6 Class on which the experiment classes are built on

Super class

mlexperiments::MLBase -> MLExperimentsBase

Public fields

learner_args

A list containing the parameter settings of the learner algorithm.

learner

An initialized learner object that inherits from class "MLLearnerBase".

Methods

Public methods

• MLExperimentsBase$new()

• MLExperimentsBase$set_data()

• MLExperimentsBase$clone()

Method new()

Create a new MLExperimentsBase object.

Usage

MLExperimentsBase$new(learner, seed, ncores = -1L)

Arguments

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).

Returns

A new MLExperimentsBase R6 object.

Method set_data()

Set the data for the experiment.

Usage

MLExperimentsBase$set_data(x, y, cat_vars = NULL)

Arguments

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).

Returns

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.

Method clone()

The objects of this class are cloneable with this method.

Usage

MLExperimentsBase$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.