find_a_violated_label

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

find_a_violated_label function

<dl><dt>alpha</dt>
<dd>classifier weights</dd>
<dt>K</dt>
<dd>kernel matrix</dd>
<dt>y</dt>
<dd>label vector</dd>
<dt>ind_y</dt>
<dd>Labeled/Unlabeled indicator</dd>
<dt>lr</dt>
<dd>positive ratio</dd>
<dt>y_init</dt>
<dd>label initialization</dd></dl>

Arguments

Find a violated label — find_a_violated_label

<dl>

<dt>alpha</dt>
<dd>classifier weights</dd>


<dt>K</dt>
<dd>kernel matrix</dd>


<dt>y</dt>
<dd>label vector</dd>


<dt>ind_y</dt>
<dd>Labeled/Unlabeled indicator</dd>


<dt>lr</dt>
<dd>positive ratio</dd>


<dt>y_init</dt>
<dd>label initialization</dd>

</dl>

find_a_violated_label: Find a violated label

Description

Usage

Arguments