expand_steps

Create a grid of parameter values from all combinations of lists supplied for
steps of a preprocessing recipe.

Meta-package for statistical and machine learning with a unified
interface for model fitting, prediction, performance assessment, and
presentation of results.  Approaches for model fitting and prediction of
numerical, categorical, or censored time-to-event outcomes include
traditional regression models, regularization methods, tree-based methods,
support vector machines, neural networks, ensembles, data preprocessing,
filtering, and model tuning and selection.  Performance metrics are provided
for model assessment and can be estimated with independent test sets, split
sampling, cross-validation, or bootstrap resampling.  Resample estimation
can be executed in parallel for faster processing and nested in cases of
model tuning and selection.  Modeling results can be summarized with
descriptive statistics; calibration curves; variable importance; partial
dependence plots; confusion matrices; and ROC, lift, and other performance
curves.

Brian Smith

MachineShop

Machine Learning Models and Tools

expand_steps function

<dl><dt>...</dt>
<dd>one or more lists containing parameter values over which to create
the grid. For each list an argument name should be given as the <code>id</code>
of the <a href="https://recipes.tidymodels.org/reference/recipe.html">recipe</a> step to which it corresponds.</dd>
<dt>random</dt>
<dd>number of points to be randomly sampled from the parameter grid
or <code>FALSE</code> if all points are to be returned.</dd></dl>

Arguments

Recipe Step Parameters Expansion — expand_steps

<dl>

<dt>...</dt>
<dd>one or more lists containing parameter values over which to create
the grid. For each list an argument name should be given as the <code>id</code>
of the <a href='https://recipes.tidymodels.org/reference/recipe.html'>recipe</a> step to which it corresponds.</dd>


<dt>random</dt>
<dd>number of points to be randomly sampled from the parameter grid
or <code>FALSE</code> if all points are to be returned.</dd>

</dl>

expand_steps: Recipe Step Parameters Expansion

Description

Usage

Value

Arguments

See Also

Examples