learnerArgsToControl

[<code>function</code>]
Function that creates control structure.

control

[any]
Arguments for control structure function.

Find all elements in <code>...</code> which are not missing and
call <code>control</code> on them.

Interface to a large number of classification and regression
techniques, including machine-readable parameter descriptions. There is
also an experimental extension for survival analysis, clustering and
general, example-specific cost-sensitive learning. Generic resampling,
including cross-validation, bootstrapping and subsampling. Hyperparameter
tuning with modern optimization techniques, for single- and multi-objective
problems. Filter and wrapper methods for feature selection. Extension of
basic learners with additional operations common in machine learning, also
allowing for easy nested resampling. Most operations can be parallelized.

learnerArgsToControl: Convert arguments to control structure.

Description

Usage

Arguments

Value