compareTo

Compare a list of learning methods (or run only one), on data/target.

The 'agghoo' procedure is an alternative to usual cross-validation.
Instead of choosing the best model trained on V subsamples, it determines
a winner model for each subsample, and then aggregates the V outputs.
For the details, see "Aggregated hold-out" by Guillaume Maillard,
Sylvain Arlot, Matthieu Lerasle (2021) <arXiv:1909.04890>
published in Journal of Machine Learning Research 22(20):1--55.

Benjamin Auder

agghoo

Aggregated Hold-Out Cross Validation

Sylvain Arlot

Melina Gallopin

Matthieu Lerasle

Guillaume Maillard

compareTo function

<dl><dt>data</dt>
<dd>Data matrix or data.frame</dd>
<dt>target</dt>
<dd>Target vector (generally)</dd>
<dt>method_s</dt>
<dd>Either a single function, or a list
(examples: agghoo_run, standardCV_run)</dd>
<dt>rseed</dt>
<dd>Seed of the random generator (-1 means "random seed")</dd>
<dt>floss</dt>
<dd>Loss function to compute the error on testing dataset.</dd>
<dt>verbose</dt>
<dd>TRUE to request methods to be verbose.</dd>
<dt>...</dt>
<dd>arguments passed to method_s function(s)</dd></dl>

Arguments

compareTo — compareTo

<dl>

<dt>data</dt>
<dd>Data matrix or data.frame</dd>


<dt>target</dt>
<dd>Target vector (generally)</dd>


<dt>method_s</dt>
<dd>Either a single function, or a list
(examples: agghoo_run, standardCV_run)</dd>


<dt>rseed</dt>
<dd>Seed of the random generator (-1 means "random seed")</dd>


<dt>floss</dt>
<dd>Loss function to compute the error on testing dataset.</dd>


<dt>verbose</dt>
<dd>TRUE to request methods to be verbose.</dd>


<dt>...</dt>
<dd>arguments passed to method_s function(s)</dd>

</dl>

compareTo: compareTo

Description

Usage

Arguments