add_missinglabels_mar

Original labels are saved in attribute <code>y_true</code>

A collection of implementations of semi-supervised classifiers
and methods to evaluate their performance. The package includes implementations
of, among others, Implicitly Constrained Learning, Moment Constrained Learning,
the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic
Likelihood estimation, S4VM and WellSVM.

Jesse Krijthe

RSSL

Implementations of Semi-Supervised Learning Approaches for
Classification

add_missinglabels_mar function

<dl><dt>df</dt>
<dd>data.frame; Data frame of interest</dd>
<dt>formula</dt>
<dd>formula; Formula to indicate the outputs</dd>
<dt>prob</dt>
<dd>numeric; Probability of removing the label</dd></dl>

Arguments

Throw out labels at random — add_missinglabels_mar

<dl>

<dt>df</dt>
<dd>data.frame; Data frame of interest</dd>


<dt>formula</dt>
<dd>formula; Formula to indicate the outputs</dd>


<dt>prob</dt>
<dd>numeric; Probability of removing the label</dd>

</dl>

add_missinglabels_mar: Throw out labels at random

Description

Usage

Arguments

See Also