Fuses a base learner with a preprocessing method. Creates a learner object, which can be
used like any other learner object, but which internally preprocesses the data as requested.
If the train or predict function is called on data / a task, the preprocessing is always performed automatically.

makePreprocWrapper

Interface to a large number of classification and regression
    techniques, including machine-readable parameter descriptions. There is
    also a n experimental extension for surival analysis and cost-sensitive
    learning. 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 common in machine learning.

makePreprocWrapper: Fuse learner with preprocessing.

Description

Usage

Arguments

Value