var_cars

This is a transformation of the <code>mtcars</code> dataset from R to produce a small
dataset with each of the fundamental datatypes: logical, factor, ordered,
integer, and double. Most of the transformations are obvious, but two are
noteworthy:<ul>
<li>For the unordered factor, the country of the car manufacturer is obtained
based on the row names of <code>mtcars</code>. This <code>var_cars</code> version does not have row names.</li>
<li>For the ordered factor, gears 3, 4, and 5 are encoded as 'three', 'four',
and 'five', respectively. The text labels make it explicit that the variable
is ordinal, yet the number names make the order crystal clear.</li>
</ul>Here is the original description of the <code>mtcars</code> dataset:
The data was extracted from the 1974 Motor Trend US magazine, and comprises
fuel consumption and 10 aspects of automobile design and performance for 32
automobiles (1973--74 models).

datasets

Accumulated Local Effects (ALE) were initially developed as a model-agnostic approach for global explanations of the results of black-box machine learning algorithms. ALE has a key advantage over other approaches like partial dependency plots (PDP) and SHapley Additive exPlanations (SHAP): its values represent a clean functional decomposition of the model. As such, ALE values are not affected by the presence or absence of interactions among variables in a mode. Moreover, its computation is relatively rapid. This package rewrites the original code from the 'ALEPlot' package for calculating ALE data and it completely reimplements the plotting of ALE values. It also extends the original ALE concept to add bootstrap-based confidence intervals and ALE-based statistics that can be used for statistical inference. For more details, see Okoli, Chitu. 2023. “Statistical Inference Using Machine Learning and Classical Techniques Based on Accumulated Local Effects (ALE).” arXiv. <arXiv:2310.09877>. <doi:10.48550/arXiv.2310.09877>.

Chitu Okoli

Interpretable Machine Learning and Statistical Inference with
Accumulated Local Effects (ALE)

Dan Apley

var_cars function

A tibble with 32 observations on 12 variables.
<dl>
<dt>mpg</dt>
<dd><code>double</code>: Miles/(US) gallon</dd><dt>cyl</dt>
<dd><code>integer</code>: Number of cylinders</dd><dt>disp</dt>
<dd><code>double</code>: Displacement (cu.in.)</dd><dt>hp</dt>
<dd><code>double</code>: Gross horsepower</dd><dt>drat</dt>
<dd><code>double</code>: Rear axle ratio</dd><dt>wt</dt>
<dd><code>double</code>: Weight (1000 lbs)</dd><dt>qsec</dt>
<dd><code>double</code>: 1/4 mile time</dd><dt>vs</dt>
<dd><code>logical</code>: Engine (0 = V-shaped, 1 = straight)</dd><dt>am</dt>
<dd><code>logical</code>: Transmission (0 = automatic, 1 = manual)</dd><dt>gear</dt>
<dd><code>ordered</code>: Number of forward gears</dd><dt>carb</dt>
<dd><code>integer</code>: Number of carburetors</dd><dt>country</dt>
<dd><code>factor</code>: Country of car manufacturer</dd>
</dl>

Format

This is a transformation of the <code>mtcars</code> dataset from R to produce a small
dataset with each of the fundamental datatypes: logical, factor, ordered,
integer, and double. Most of the transformations are obvious, but two are
noteworthy:<ul>
<li>For the unordered factor, the country of the car manufacturer is obtained
based on the row names of <code>mtcars</code>. This <code>var_cars</code> version does not have row names.</li>
<li>For the ordered factor, gears 3, 4, and 5 are encoded as 'three', 'four',
and 'five', respectively. The text labels make it explicit that the variable
is ordinal, yet the number names make the order crystal clear.</li>
</ul>

Here is the original description of the <code>mtcars</code> dataset:
The data was extracted from the 1974 Motor Trend US magazine, and comprises
fuel consumption and 10 aspects of automobile design and performance for 32
automobiles (1973--74 models).

Multi-variable transformation of the mtcars dataset. — var_cars

A tibble with 32 observations on 12 variables.
<dl>
<dt>mpg</dt>
<dd><code>double</code>: Miles/(US) gallon</dd>

<dt>cyl</dt>
<dd><code>integer</code>: Number of cylinders</dd>

<dt>disp</dt>
<dd><code>double</code>: Displacement (cu.in.)</dd>

<dt>hp</dt>
<dd><code>double</code>: Gross horsepower</dd>

<dt>drat</dt>
<dd><code>double</code>: Rear axle ratio</dd>

<dt>wt</dt>
<dd><code>double</code>: Weight (1000 lbs)</dd>

<dt>qsec</dt>
<dd><code>double</code>: 1/4 mile time</dd>

<dt>vs</dt>
<dd><code>logical</code>: Engine (0 = V-shaped, 1 = straight)</dd>

<dt>am</dt>
<dd><code>logical</code>: Transmission (0 = automatic, 1 = manual)</dd>

<dt>gear</dt>
<dd><code>ordered</code>: Number of forward gears</dd>

<dt>carb</dt>
<dd><code>integer</code>: Number of carburetors</dd>

<dt>country</dt>
<dd><code>factor</code>: Country of car manufacturer</dd>


</dl>

var_cars: Multi-variable transformation of the mtcars dataset.

Description

Usage

Arguments

Format

References