describe_data

Calculate key descriptive statistics for a given set of data.

Create, visualize, and test fast-and-frugal decision trees (FFTs) using the algorithms and methods described by Phillips, Neth, Woike & Gaissmaier (2017), <doi:10.1017/S1930297500006239>.
FFTs are simple and transparent decision trees for solving binary classification problems.
FFTs can be preferable to more complex algorithms because they require very little information, are easy to understand and communicate, and are robust against overfitting.

Hansjoerg Neth

FFTrees

Generate, Visualise, and Evaluate Fast-and-Frugal Decision Trees

Nathaniel Phillips

Jan Woike

Wolfgang Gaissmaier

describe_data function

<dl><dt>data</dt>
<dd>A data frame with a criterion variable <code>criterion_name</code>.</dd>
<dt>data_name</dt>
<dd>A character string specifying a name for the data.</dd>
<dt>criterion_name</dt>
<dd>A character string specifying the criterion name.</dd>
<dt>baseline_value</dt>
<dd>The value in <code>criterion_name</code> denoting the baseline
(e.g., <code>TRUE</code> or <code>FALSE</code>).</dd></dl>

Arguments

Describe data — describe_data

<dl>

<dt>data</dt>
<dd>A data frame with a criterion variable <code>criterion_name</code>.</dd>


<dt>data_name</dt>
<dd>A character string specifying a name for the data.</dd>


<dt>criterion_name</dt>
<dd>A character string specifying the criterion name.</dd>


<dt>baseline_value</dt>
<dd>The value in <code>criterion_name</code> denoting the baseline
(e.g., <code>TRUE</code> or <code>FALSE</code>).</dd>

</dl>

describe_data: Describe data

Description

Usage

Value

Arguments

Examples