olive

contains 572 observations and 10 variables<dl>
<dt>Region</dt>
<dd>Three super-classes of Italy: North, South and the island of Sardinia</dd><dt>area</dt>
<dd>Nine collection areas: three from North, four from South and 2 from Sardinia</dd>
 
<dt>palmitic</dt>
<dd>fatty acids percent x 100</dd><dt>palmitoleic</dt>
<dd>fatty acids percent x 100</dd><dt>stearic</dt>
<dd>fatty acids percent x 100</dd><dt>oleic</dt>
<dd>fatty acids percent x 100</dd><dt>linoleic</dt>
<dd>fatty acids percent x 100</dd><dt>linolenic</dt>
<dd>fatty acids percent x 100</dd><dt>arachidic</dt>
<dd>fatty acids percent x 100</dd><dt>eicosenoic</dt>
<dd>fatty acids percent x 100</dd>
</dl>

datasets

Implements extensions to the projection pursuit tree algorithm for supervised classification, see Lee, Y. (2013), <doi:10.1214/13-EJS810> and Lee, E-K. (2018) <doi:10.18637/jss.v083.i08>. The algorithm is changed in two ways: improving prediction boundaries by modifying the choice of split points-through class subsetting; and increasing flexibility by allowing multiple splits per group.

Natalia Silva

PPtreeExt

Projection Pursuit Classification Tree Extensions

Natalia da Silva

Dianne Cook

Eun-Kyung Lee

olive function

A data frame contains 573 observations and 10 variables

Format

contains 572 observations and 10 variables<dl>
<dt>Region</dt>
<dd>Three super-classes of Italy: North, South and the island of Sardinia</dd>

<dt>area</dt>
<dd>Nine collection areas: three from North, four from South and 2 from Sardinia</dd>
 
<dt>palmitic</dt>
<dd>fatty acids percent x 100</dd>

<dt>palmitoleic</dt>
<dd>fatty acids percent x 100</dd>

<dt>stearic</dt>
<dd>fatty acids percent x 100</dd>

<dt>oleic</dt>
<dd>fatty acids percent x 100</dd>

<dt>linoleic</dt>
<dd>fatty acids percent x 100</dd>

<dt>linolenic</dt>
<dd>fatty acids percent x 100</dd>

<dt>arachidic</dt>
<dd>fatty acids percent x 100</dd>

<dt>eicosenoic</dt>
<dd>fatty acids percent x 100</dd>


</dl>

olive: The olive data set

Description

Usage

Arguments

Format