getStackedBaseLearnerPredictions

[<code>WrappedModel</code>] Wrapped model, result of train.

model

[<code>data.frame</code>]
New observations, for which the predictions using the specified base learners should be returned.
Default is <code>NULL</code> and extracts the base learner predictions that were made during the training.

newdata


Returns the predictions for each base learner.


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.

getStackedBaseLearnerPredictions: Returns the predictions for each base learner.

Description

Usage

Arguments

Details