missing_labels

Access the true labels for the objects with missing labels when they are stored as an attribute in a data frame

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

missing_labels function

<dl><dt>df</dt>
<dd>data.frame; data.frame with y_true attribute</dd></dl>

Arguments

Access the true labels for the objects with missing labels when they are stored as an attribute in a data frame — missing_labels

<dl>

<dt>df</dt>
<dd>data.frame; data.frame with y_true attribute</dd>

</dl>

missing_labels: Access the true labels for the objects with missing labels when they are stored as an attribute in a data frame

Description

Usage

Arguments

See Also