setup_SpectralLocal

Setup a <code>SpectralLocalConfig</code> object for spectral clustering with a locally
scaled Gaussian kernel, via the 'kernlab' package. Each case's kernel width
is taken from the distance to its seventh nearest neighbor, which lets one
clustering hold groups of differing density. The per-case widths need every
pairwise distance, so this variant has no Nystrom approximation.

Machine learning and visualization package with an 'S7' backend featuring
comprehensive type checking and validation, observable runs, and auditable outputs.
The functional API provides one-call access to supervised and unsupervised learning
through train(), cluster(), and decomp(). All configuration steps are performed using
setup functions and validated. A single call to train() can handle preprocessing,
decomposition, hyperparameter tuning, model stacking, and testing with nested resampling.
Supports 'data.frame', 'data.table', and 'tibble' inputs and parallel execution. Plot
methods for trained and resampled supervised models draw interactive figures through
'rtemis.draw'. Includes native implementations of SuperLearner, RuleFit, and Linear
Additive Trees, and supports conformal prediction. The package first appeared in
E.D. Gennatas (2017)
<https://repository.upenn.edu/entities/publication/d81892ea-3087-4b71-a6f5-739c58626d64>.

Efstathios D. Gennatas

rtemis

Schema-Driven Machine Learning and Visualization

E.D. Gennatas

setup_SpectralLocal function

<dl><dt>k</dt>
<dd>Integer [2, Inf): Number of clusters. Must be no more than the number of cases.</dd>
<dt>iterations</dt>
<dd>Integer [1, Inf): Maximum number of k-means iterations run on the spectral embedding.</dd>
<dt>features</dt>
<dd>Optional Character vector: Names of at least 2 distinct
feature columns to cluster on. <code>NULL</code> clusters on all numeric features.</dd></dl>

Arguments

Author

Setup SpectralLocalConfig — setup_SpectralLocal

<dl>

<dt>k</dt>
<dd>Integer [2, Inf): Number of clusters. Must be no more than the number of cases.</dd>


<dt>iterations</dt>
<dd>Integer [1, Inf): Maximum number of k-means iterations run on the spectral embedding.</dd>


<dt>features</dt>
<dd>Optional Character vector: Names of at least 2 distinct
feature columns to cluster on. <code>NULL</code> clusters on all numeric features.</dd>

</dl>

setup_SpectralLocal: Setup SpectralLocalConfig

Description

Usage

Value

Arguments

Author

Details

References

Examples