tunable_tdavec

tunable.step_vpd_algebraic_functions

tunable.step_vpd_betti_curve

tunable.step_vpd_complex_polynomial

tunable.step_vpd_descriptive_statistics

tunable.step_vpd_euler_characteristic_curve

tunable.step_vpd_normalized_life_curve

tunable.step_vpd_persistence_block

tunable.step_vpd_persistence_image

tunable.step_vpd_persistence_landscape

tunable.step_vpd_persistence_silhouette

tunable.step_vpd_persistent_entropy_summary

tunable.step_vpd_tent_template_functions

tunable.step_vpd_tropical_coordinates

These functions define what parameters can be tuned for
specific steps. They also define the recommended objects from
<a href="https://dials.tidymodels.org/reference/dials-package.html">dials</a> that can be used to generate new parameter
values and other characteristics.

internal

Topological data analytic methods in machine learning rely on
vectorizations of the persistence diagrams that encode persistent
homology, as surveyed by Ali &al (2000)
<doi:10.48550/arXiv.2212.09703>. Persistent homology can be computed
using 'TDA' and 'ripserr' and vectorized using 'TDAvec'. The
Tidymodels package collection modularizes machine learning in R for
straightforward extensibility; see Kuhn & Silge (2022,
ISBN:978-1-4920-9644-3). These 'recipe' steps and 'dials' tuners make
efficient algorithms for computing and vectorizing persistence
diagrams available for Tidymodels workflows.

Jason Cory Brunson

tdarec

A 'recipes' Extension for Persistent Homology and Its
Vectorizations

tunable_tdavec function

<dl><dt>x</dt>
<dd>A recipe step object</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

These functions define what parameters can be tuned for
specific steps. They also define the recommended objects from
<a href='https://dials.tidymodels.org/reference/dials-package.html'>dials</a> that can be used to generate new parameter
values and other characteristics.

tunable() methods for tdavec package — tunable_tdavec

<dl>

<dt>x</dt>
<dd>A recipe step object</dd>


<dt>...</dt>
<dd>Not used.</dd>

</dl>

<code>tunable()</code> methods for tdavec package

tunable_tdavec: `tunable()` methods for tdavec package

Description

Usage

Value

Arguments