fftrees_apply

Applies a fast-and-frugal tree to a dataset and generates several accuracy statistics

internal

Create, visualize, and test fast-and-frugal decision trees (FFTs) using methods described in Phillips, Neth, Woike & Gaissmaier. (2017). FFTs are very simple decision trees for
binary classification problems. FFTs can be preferable to more complex algorithms because they are easy to communicate,
require very little information, and are robust against overfitting.

Nathaniel Phillips

FFTrees

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

Hansjoerg Neth

Jan Woike

Wolfgang Gaissmaer

fftrees_apply function

<dl><dt>x</dt>
<dd>FFTrees.</dd>
<dt>mydata</dt>
<dd>dataframe.</dd>
<dt>newdata</dt>
<dd>dataframe.</dd>
<dt>allNA.pred</dt>
<dd>logical. What should be predicted if all cue values in tree are NA? Default is FALSE</dd></dl>

Arguments

Applies a fast-and-frugal tree to a dataset and generates several accuracy statistics — fftrees_apply

<dl>

<dt>x</dt>
<dd>FFTrees.</dd>


<dt>mydata</dt>
<dd>dataframe.</dd>


<dt>newdata</dt>
<dd>dataframe.</dd>


<dt>allNA.pred</dt>
<dd>logical. What should be predicted if all cue values in tree are NA? Default is FALSE</dd>

</dl>

fftrees_apply: Applies a fast-and-frugal tree to a dataset and generates several accuracy statistics

Description

Usage

Value

Arguments