model_control

Specifies cross-validation settings for the <code>model</code> function.

Functions for dissimilarity analysis and machine learning in complex
spectral data sets, including memory-based learning (MBL), optimal subset
search and selection, and retrieval-based modelling with model libraries.
Supports local learning, optimisation of spectral libraries, and
ensemble prediction from precomputed models. Most of these functions are
based on the methods presented in Ramirez-Lopez et al. (2013)
<doi:10.1016/j.geoderma.2012.12.014>, Ramirez-Lopez et al. (2026a)
<doi:10.1016/j.aca.2026.345682>, and Ramirez-Lopez et al. (2026b)
<doi:10.1016/j.aca.2026.345651>.

Leonardo RamirezLopez

resemble

Similarity Retrieval and Local Learning for Spectral
Chemometrics

Leonardo Ramirez-Lopez

Antoine Stevens

Claudio Orellano

model_control function

<dl><dt>validation_type</dt>
<dd>a character string specifying the validation method:<ul>
<li><code>"lgo"</code>: Leave-group-out cross-validation. At each iteration,
a proportion <code>p</code> of observations is retained for training and the
remainder is used for validation. This is repeated <code>number</code> times.</li>
<li><code>"none"</code>: No cross-validation is performed.</li>
</ul></dd>
<dt>number</dt>
<dd>an integer indicating the number of cross-validation
iterations. Only used when <code>validation_type = "lgo"</code>. Default is 10.</dd>
<dt>p</dt>
<dd>a numeric value between 0 and 1 indicating the proportion of
observations to retain for training at each cross-validation iteration.
Only used when <code>validation_type = "lgo"</code>. Default is 0.75.</dd></dl>

Arguments

<a href="https://orcid.org/0000-0002-5369-5120">Leonardo Ramirez-Lopez</a>

Author

Control parameters for global model fitting — model_control

<dl>

<dt>validation_type</dt>
<dd>a character string specifying the validation method:<ul>
<li><code>"lgo"</code>: Leave-group-out cross-validation. At each iteration,
a proportion <code>p</code> of observations is retained for training and the
remainder is used for validation. This is repeated <code>number</code> times.</li>
<li><code>"none"</code>: No cross-validation is performed.</li>
</ul></dd>


<dt>number</dt>
<dd>an integer indicating the number of cross-validation
iterations. Only used when <code>validation_type = "lgo"</code>. Default is 10.</dd>


<dt>p</dt>
<dd>a numeric value between 0 and 1 indicating the proportion of
observations to retain for training at each cross-validation iteration.
Only used when <code>validation_type = "lgo"</code>. Default is 0.75.</dd>

</dl>

<a href='https://orcid.org/0000-0002-5369-5120'>Leonardo Ramirez-Lopez</a>

model_control: Control parameters for global model fitting

Description

Usage

Value

Arguments

Author

See Also

Examples