adjacency_knn

Calculates symmetric adjacency: objects are neighbours is either one of them is in the set of nearest neighbours of the other.

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

adjacency_knn function

<dl><dt>X</dt>
<dd>matrix; input matrix</dd>
<dt>distance</dt>
<dd>character; distance metric used in the <code>dist</code> function</dd>
<dt>k</dt>
<dd>integer; Number of neighbours</dd></dl>

Arguments

Calculate knn adjacency matrix — adjacency_knn

<dl>

<dt>X</dt>
<dd>matrix; input matrix</dd>


<dt>distance</dt>
<dd>character; distance metric used in the <code>dist</code> function</dd>


<dt>k</dt>
<dd>integer; Number of neighbours</dd>

</dl>

adjacency_knn: Calculate knn adjacency matrix

Description

Usage

Value

Arguments