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<html><head><title>R: K-NEAREST NEIGHBOR CLASSIFIERS WITHIN LEAVES OF A TREE</title>
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<table width="100%" summary="page for knnTree {knnTree}"><tr><td>knnTree {knnTree}</td><td align="right">R Documentation</td></tr></table>
<h2>K-NEAREST NEIGHBOR CLASSIFIERS WITHIN LEAVES OF A TREE</h2>
<h3>Description</h3>
<p>
Construct or predict with a knnTree object, which is
a set of k-nearest neighbor classifiers, one for each leaf of a tree.
</p>
<h3>Usage</h3>
<pre>knnTree (trg.set, trg.classes, v = 10,
k.vec = seq(1, 31, by = 2), seed = 0, opt.tree = "ignore",
opt.tree.size = 4, scaling = 1, prune.function = prune.misclass,
one.SE = TRUE, backward = FALSE, max.steps=-1, v.start = 1, leaf.start = 1,
verbose = FALSE, debug = 0, fname = "", use.big = FALSE, save.output = "")
</pre>
<h3>Arguments</h3>
<table summary="R argblock">
<tr valign="top"><td><code>trg.set</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>trg.classes</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>v</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>k.vec</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>seed</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>opt.tree</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>opt.tree.size</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>scaling</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>prune.function</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>one.SE</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>backward</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>max.steps</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>v.start</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>leaf.start</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>verbose</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>debug</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>fname</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>use.big</code></td>
<td>
</td></tr>
<tr valign="top"><td><code>save.output</code></td>
<td>
</td></tr>
</table>
<p>
{character; if not empty, the resulting object is
assigned to results in frame 1 and also dumped to disk
in the file named in save.output. This can be useful for parallel
processing.}</p>
<h3>Value</h3>
<p>
Object of class knnTree. If the tree has n leaves, this will
be a list with n+2 elements. The first is the global tree. The next n
elements are the n individual knn.var objects, one per leaf. Each of these
objects has two additional pieces: leaf (giving the leaf number) and
where (giving the row number of the global tree's frame for this leaf).
The n+2-th element of the list is named call and is the call used to
create the object.</p>
<hr><div align="center">[Package <em>knnTree</em> version 1.2.4 <a href="00Index.html">Index]</a></div>
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