Get a description of all possible parameter settings for
  a learner.

getParamSet

Interface to a large number of classification and
        regression techniques, including machine-readable parameter
        descriptions. Generic resampling, including cross-validation,
        bootstrapping and subsampling. Hyperparameter tuning with
        modern optimization techniques. Filter and wrapper methods for
        feature selection. Extension of basic learners with additional
        operations. Nested resampling.

getParamSet: Get a description of all possible parameter settings for a learner.

Description

Usage

Arguments

Value