losslogsum

losslogsum,NormalBasedClassifier-method

LogsumLoss of a classifier or regression function

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

losslogsum function

<dl><dt>object</dt>
<dd>Classifier or Regression object</dd>
<dt>...</dt>
<dd>Additional parameters</dd>
<dt>newdata</dt>
<dd>Design matrix of labeled objects</dd>
<dt>Y</dt>
<dd>label matrix of labeled objects</dd>
<dt>X_u</dt>
<dd>Design matrix of unlabeled objects</dd>
<dt>Y_u</dt>
<dd>label matrix of unlabeled objects</dd></dl>

Arguments

LogsumLoss of a classifier or regression function — losslogsum

<dl>

<dt>object</dt>
<dd>Classifier or Regression object</dd>


<dt>...</dt>
<dd>Additional parameters</dd>


<dt>newdata</dt>
<dd>Design matrix of labeled objects</dd>


<dt>Y</dt>
<dd>label matrix of labeled objects</dd>


<dt>X_u</dt>
<dd>Design matrix of unlabeled objects</dd>


<dt>Y_u</dt>
<dd>label matrix of unlabeled objects</dd>

</dl>

losslogsum: LogsumLoss of a classifier or regression function

Description

Usage

Arguments