fftrees_apply

<code>fftrees_apply</code> applies a fast-and-frugal tree (FFT, as an <code>FFTrees</code> object)
to a dataset and generates corresponding accuracy statistics.
<code>fftrees_apply</code> is called internally by the main <code>FFTrees</code> function
(with <code>mydata = "train"</code> and --- if test data exists --- <code>mydata = "test"</code>)
and when predicting outcomes for new data by <code>predict.FFTrees</code>.

internal

Create, visualize, and test fast-and-frugal decision trees (FFTs) using the algorithms and methods described in Phillips, Neth, Woike & Gaissmaier (2017).
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 communicate, and are robust against overfitting.

Hansjoerg Neth

FFTrees

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

Nathaniel Phillips

Jan Woike

Wolfgang Gaissmaier

fftrees_apply function

<dl><dt>x</dt>
<dd>An FFT to apply (as an <code>FFTrees</code> object).</dd>
<dt>mydata</dt>
<dd>character. Data type to which FFT should be applied (either <code>"train"</code> or <code>"test"</code>).</dd>
<dt>newdata</dt>
<dd>dataframe. New data to which FFT should be applied.</dd>
<dt>allNA.pred</dt>
<dd>logical. What should be predicted if all cue values in tree are NA? Default is <code>FALSE</code>.</dd></dl>

Arguments

Apply an FFT to data and generate accuracy statistics — fftrees_apply

<dl>

<dt>x</dt>
<dd>An FFT to apply (as an <code>FFTrees</code> object).</dd>


<dt>mydata</dt>
<dd>character. Data type to which FFT should be applied (either <code>"train"</code> or <code>"test"</code>).</dd>


<dt>newdata</dt>
<dd>dataframe. New data to which FFT should be applied.</dd>


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

</dl>

fftrees_apply: Apply an FFT to data and generate accuracy statistics

Description

Usage

Value

Arguments

See Also