testa_KNN

Implements the kK-NN algorithm, an adaptive k-nearest neighbor classifier that adjusts the neighborhood size based on local data curvature. The method estimates local Gaussian curvature by approximating the shape operator of the data manifold. This approach aims to improve classification performance, particularly in datasets with limited samples.

Gabriel Pereira

LCCkNN

Adaptive k-Nearest Neighbor Classifier Based on Local Curvature
Estimation

testa_KNN function

<dl><dt>train</dt>
<dd>A numeric matrix or data frame of the training data.</dd>
<dt>test</dt>
<dd>A numeric matrix or data frame of the test data.</dd>
<dt>train_target</dt>
<dd>A numeric or factor vector of class labels for the training data.</dd>
<dt>nn</dt>
<dd>The number of neighbors.</dd></dl>

Arguments

Standard k-NN classifier. — testa_KNN

<dl>

<dt>train</dt>
<dd>A numeric matrix or data frame of the training data.</dd>


<dt>test</dt>
<dd>A numeric matrix or data frame of the test data.</dd>


<dt>train_target</dt>
<dd>A numeric or factor vector of class labels for the training data.</dd>


<dt>nn</dt>
<dd>The number of neighbors.</dd>

</dl>

testa_KNN: Standard k-NN classifier.

Description

Usage

Value

Arguments