summarizeLevels

[<code>data.frame</code> | <code><a rd-options="" href="/link/Task?package=mlr&version=2.10" data-mini-rdoc="mlr::Task">Task</a></code>]
Input data.

[<code>character</code>]
Restrict result to columns in <code>cols</code>.
Default is all factor, character and logical columns of <code>obj</code>.

cols

Characters and logicals will be treated as factors.

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

summarizeLevels function

[<code>data.frame</code> | <code><a rd-options='' href='Task'>Task</a></code>]
Input data.

summarizeLevels: Summarizes factors of a data.frame by tabling them.

Description

Usage

Arguments

Value