training


A simulated data set of symptoms of breast cancer patients


datasets

Aimed at applying the Harvest classification tree algorithm, modified algorithm of classic classification tree.The harvested tree has advantage of deleting redundant rules in trees, leading to a simplify and more efficient tree model.It was firstly used in drug discovery field, but it also performs well in other kinds of data, especially when the region of a class is disconnected. This package also improves the basic harvest classification tree algorithm by extending the field of data of algorithm to both continuous and categorical variables. To learn more about the harvest classification tree algorithm, you can go to http://www.stat.ubc.ca/Research/TechReports/techreports/220.pdf for more information.

Bingyuan Liu

Harvest.Tree

Harvest the Classification Tree

training function

A data frame with 300 observations on the following 5 variables.
  <dl>
    <dt><code>y</code></dt><dd>a numeric vector</dd> <dt><code>x1</code></dt><dd>a factor with levels <code>21</code> <code>22</code> <code>23</code> <code>24</code> <code>25</code> <code>26</code> <code>27</code> <code>28</code> <code>29</code></dd> <dt><code>x2</code></dt><dd>a factor with levels <code>39-</code> <code>40-49</code> <code>50-69</code> <code>70-74</code> <code>75+</code></dd> <dt><code>x3</code></dt><dd>a numeric vector</dd> <dt><code>x4</code></dt><dd>a factor with levels <code>2004</code> <code>2005</code> <code>2006</code> <code>2007</code> <code>2008</code> <code>2009</code> <code>2010</code></dd> </dl> 

Format

simulated data for breast cancer diagnosis

training: training

Description

Usage

Arguments

Format

Source