posterior

posterior,NormalBasedClassifier-method

posterior,LogisticRegression-method

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

posterior function

<dl><dt>object</dt>
<dd>Classifier or Regression object</dd>
<dt>...</dt>
<dd>Additional parameters</dd>
<dt>newdata</dt>
<dd>matrix of dataframe of objects to be classified</dd></dl>

Arguments

Class Posteriors of a classifier — posterior

<dl>

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


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


<dt>newdata</dt>
<dd>matrix of dataframe of objects to be classified</dd>

</dl>

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posterior: Class Posteriors of a classifier

Description

Usage

Arguments