autoplot.posterior_diff

A density is created for each contrast in a faceted grid.

Bayesian analysis used here to answer the question: "when
looking at resampling results, are the differences between models
'real'?" To answer this, a model can be created were the performance
statistic is the resampling statistics (e.g. accuracy or RMSE). These
values are explained by the model types. In doing this, we can get
parameter estimates for each model's affect on performance and make
statistical (and practical) comparisons between models. The methods
included here are similar to Benavoli et al (2017)
<https://jmlr.org/papers/v18/16-305.html>.

Max Kuhn

tidyposterior

Bayesian Analysis to Compare Models using Resampling Statistics

Posit Software, PBC 

autoplot.posterior_diff function

<dl><dt>object</dt>
<dd>An object produced by <code>contrast_models()</code>.</dd>
<dt>size</dt>
<dd>The size of an effective difference. For example, a
5\
"real" difference.</dd>
<dt>...</dt>
<dd>Options passed to <code>geom_line(stat = "density", ...)</code>.</dd></dl>

Arguments

Visualize the Posterior Distributions of Model Differences — autoplot.posterior_diff

<dl>

<dt>object</dt>
<dd>An object produced by <code>contrast_models()</code>.</dd>


<dt>size</dt>
<dd>The size of an effective difference. For example, a
5\
"real" difference.</dd>


<dt>...</dt>
<dd>Options passed to <code>geom_line(stat = "density", ...)</code>.</dd>

</dl>

autoplot.posterior_diff: Visualize the Posterior Distributions of Model Differences

Description

Usage

Value

Arguments

Examples