losspart

losspart,NormalBasedClassifier-method

Loss of a classifier or regression function evaluated on partial labels

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

losspart function

<dl><dt>object</dt>
<dd>Classifier; Trained Classifier</dd>
<dt>...</dt>
<dd>additional parameters</dd>
<dt>newdata</dt>
<dd>design matrix</dd>
<dt>Y</dt>
<dd>class responsibility matrix</dd></dl>

Arguments

Loss of a classifier or regression function evaluated on partial labels — losspart

<dl>

<dt>object</dt>
<dd>Classifier; Trained Classifier</dd>


<dt>...</dt>
<dd>additional parameters</dd>


<dt>newdata</dt>
<dd>design matrix</dd>


<dt>Y</dt>
<dd>class responsibility matrix</dd>

</dl>

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losspart: Loss of a classifier or regression function evaluated on partial labels

Description

Usage

Arguments