heart.test

<p>Testing data for a <code>heartdisease</code> data.
This subset is used to test the prediction performance of a model trained on the <code>heart.train</code> data.
The dataset <code>heartdisease</code> contains both datasets.</p>

datasets

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

heart.test function

<p>A data frame containing 153 rows and 14 columns (see <code>heartdisease</code> for details).</p>

Format

Heart disease testing data — heart.test

Heart disease testing data

heart.test: Heart disease testing data

Description

Usage

Arguments

Format

See Also