supermarket1996

datasets

Implements the SVM-Maj algorithm to train data with support vector machine
as described in Groenen et al. (2008) <doi:10.1007/s11634-008-0020-9>.
This algorithm uses two efficient updates, one for linear kernel and one
for the nonlinear kernel.

Hok San Yip

SVMMaj

Implementation of the SVM-Maj Algorithm

supermarket1996 function

This dataframe contains the following columns<ul>
<li>STOREIdentifier of the store</li>
<li>CITYThe city of the store</li>
<li>ZIPThe zip code of the store</li>
<li>GROCERY_sum</li>
<li>GROCCOUP_sum</li>
<li>AGE9</li>
<li>AGE60</li>
<li>ETHNIC</li>
<li>EDUC</li>
<li>NOCAR</li>
<li>INCOME</li>
<li>INCSIGMA</li>
<li>HSIZEAVG</li>
<li>HSIZE1</li>
<li>HSIZE2</li>
<li>HSIZE34</li>
<li>HSIZE567</li>
<li>HH3PLUS</li>
<li>HH4PLUS</li>
<li>HHSINGLE</li>
<li>HHLARGE</li>
<li>WORKWOM</li>
<li>SINHOUSE</li>
<li>DENSITY</li>
<li>HVAL150</li>
<li>HVAL200</li>
<li>HVALMEAN</li>
<li>SINGLE</li>
<li>RETIRED</li>
<li>UNEMP</li>
<li>WRKCH5</li>
<li>WRKCH17</li>
<li>NWRKCH5</li>
<li>NWRKCH17</li>
<li>WRKCH</li>
<li>NWRKCH</li>
<li>WRKWCH</li>
<li>WRKWNCH</li>
<li>TELEPHN</li>
<li>MORTGAGE</li>
<li>NWHITE</li>
<li>POVERTY</li>
<li>SHPCONS</li>
<li>SHPHURR</li>
<li>SHPAVID</li>
<li>SHPKSTR</li>
<li>SHPUNFT</li>
<li>SHPBIRD</li>
<li>SHOPINDX</li>
<li>SHPINDX</li>
</ul>

supermarket1996: Supermarket data 1996

Description

Arguments

Format

Examples