makeDownsampleWrapper

[<code><a rd-options="" href="/link/Learner?package=mlr&version=2.10" data-mini-rdoc="mlr::Learner">Learner</a></code> | <code>character(1)</code>]
The learner.
If you pass a string the learner will be created via <code><a rd-options="" href="/link/makeLearner?package=mlr&version=2.10" data-mini-rdoc="mlr::makeLearner">makeLearner</a></code>.

learner

[<code>numeric(1)</code>]
See <code><a rd-options="" href="/link/downsample?package=mlr&version=2.10" data-mini-rdoc="mlr::downsample">downsample</a></code>.
Default is 1.

dw.perc

[<code>logical(1)</code>]
See <code><a rd-options="" href="/link/downsample?package=mlr&version=2.10" data-mini-rdoc="mlr::downsample">downsample</a></code>.
Default is <code>FALSE</code>.

dw.stratify

Creates a learner object, which can be
used like any other learner object.
It will only be trained on a subset of the original data to save computational time.

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.

Bernd Bischl

Machine Learning in R

makeDownsampleWrapper function

[<code><a rd-options='' href='Learner'>Learner</a></code> | <code>character(1)</code>]
The learner.
If you pass a string the learner will be created via <code><a rd-options='' href='makeLearner'>makeLearner</a></code>.

[<code>numeric(1)</code>]
See <code><a rd-options='' href='downsample'>downsample</a></code>.
Default is 1.

[<code>logical(1)</code>]
See <code><a rd-options='' href='downsample'>downsample</a></code>.
Default is <code>FALSE</code>.

makeDownsampleWrapper: Fuse learner with simple downsampling (subsampling).

Description

Usage

Arguments

Value

See Also