stop_iter

For some models, the effectiveness of the model can decrease as training
iterations continue. <code>stop_iter()</code> can be used to tune how many iterations
without an improvement in the objective function occur before training should
be halted.

Many models contain tuning parameters (i.e. parameters that
cannot be directly estimated from the data). These tools can be used
to define objects for creating, simulating, or validating values for
such parameters.

Hannah Frick

dials

Tools for Creating Tuning Parameter Values

Max Kuhn

Posit Software, PBC 

stop_iter function

<dl><dt>range</dt>
<dd>A two-element vector holding the defaults for the smallest and
largest possible values, respectively. If a transformation is specified,
these values should be in the transformed units.</dd>
<dt>trans</dt>
<dd>A <code>trans</code> object from the <code>scales</code> package, such as
<code>scales::transform_log10()</code> or <code>scales::transform_reciprocal()</code>. If not provided,
the default is used which matches the units used in <code>range</code>. If no
transformation, <code>NULL</code>.</dd></dl>

Arguments

Early stopping parameter — stop_iter

<dl>

<dt>range</dt>
<dd>A two-element vector holding the defaults for the smallest and
largest possible values, respectively. If a transformation is specified,
these values should be in the transformed units.</dd>


<dt>trans</dt>
<dd>A <code>trans</code> object from the <code>scales</code> package, such as
<code>scales::transform_log10()</code> or <code>scales::transform_reciprocal()</code>. If not provided,
the default is used which matches the units used in <code>range</code>. If no
transformation, <code>NULL</code>.</dd>

</dl>

stop_iter: Early stopping parameter

Description

Usage

Arguments

Examples