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<html><head><title>R: Multiedit for k-NN Classifier</title>
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<table width="100%" summary="page for multiedit {class}"><tr><td>multiedit {class}</td><td align="right">R Documentation</td></tr></table>
<h2>Multiedit for k-NN Classifier</h2>
<h3>Description</h3>
<p>
Multiedit for k-NN classifier
</p>
<h3>Usage</h3>
<pre>
multiedit(x, class, k = 1, V = 3, I = 5, trace = TRUE)
</pre>
<h3>Arguments</h3>
<table summary="R argblock">
<tr valign="top"><td><code>x</code></td>
<td>
matrix of training set.
</td></tr>
<tr valign="top"><td><code>class</code></td>
<td>
vector of classification of training set.
</td></tr>
<tr valign="top"><td><code>k</code></td>
<td>
number of neighbours used in k-NN.
</td></tr>
<tr valign="top"><td><code>V</code></td>
<td>
divide training set into V parts.
</td></tr>
<tr valign="top"><td><code>I</code></td>
<td>
number of null passes before quitting.
</td></tr>
<tr valign="top"><td><code>trace</code></td>
<td>
logical for statistics at each pass.
</td></tr>
</table>
<h3>Value</h3>
<p>
index vector of cases to be retained.</p>
<h3>References</h3>
<p>
P. A. Devijver and J. Kittler (1982)
<EM>Pattern Recognition. A Statistical Approach.</EM>
Prentice-Hall, p. 115.
</p>
<p>
Ripley, B. D. (1996)
<EM>Pattern Recognition and Neural Networks.</EM> Cambridge.
</p>
<p>
Venables, W. N. and Ripley, B. D. (2002)
<EM>Modern Applied Statistics with S.</EM> Fourth edition. Springer.
</p>
<h3>See Also</h3>
<p>
<code><a href="condense.html">condense</a></code>, <code><a href="reduce.nn.html">reduce.nn</a></code>
</p>
<h3>Examples</h3>
<pre>
data(iris3)
tr <- sample(1:50, 25)
train <- rbind(iris3[tr,,1], iris3[tr,,2], iris3[tr,,3])
test <- rbind(iris3[-tr,,1], iris3[-tr,,2], iris3[-tr,,3])
cl <- factor(c(rep(1,25),rep(2,25), rep(3,25)), labels=c("s", "c", "v"))
table(cl, knn(train, test, cl, 3))
ind1 <- multiedit(train, cl, 3)
length(ind1)
table(cl, knn(train[ind1, , drop=FALSE], test, cl[ind1], 1))
ntrain <- train[ind1,]; ncl <- cl[ind1]
ind2 <- condense(ntrain, ncl)
length(ind2)
table(cl, knn(ntrain[ind2, , drop=FALSE], test, ncl[ind2], 1))
</pre>
<hr><div align="center">[Package <em>class</em> version 7.2-44 <a href="00Index.html">Index]</a></div>
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