[R] k-nearest neighbour classification

[Neverstop]

Hi, I'm trying to perform a cross validation to choose the optimal k in the
k-nearest-neighbors algorithm for classification. I'm using the  knn
<http://stat.ethz.ch/R-manual/R-devel/library/class/html/knn.html>  
function of the package class. Reading the R documentation, I've found out
that there's already a function to perform cross validation:  knn.cv
<http://stat.ethz.ch/R-manual/R-devel/library/class/html/knn.cv.html>  . The
problem is that I don't understand how I should use it.

data(iris)
head(iris)
predictors.training=iris[c(1:25,51:75,101:125),c("Sepal.Length","Sepal.Width","Petal.Length","Petal.Width")]
predictors.test=iris[c(26:50,76:100,126:150),c("Sepal.Length","Sepal.Width","Petal.Length","Petal.Width")]
classes.training=iris[c(1:25,51:75,101:125),"Species"]
library(class)
knn.cv(train=predictors.training, cl=classes.training, k=c(1,3,5,7),
prob=TRUE)

Warning messages:
1: In if (ntr - 1 < k) { :
  the condition has length > 1 and only the first element will be used
2: In if (k < 1) stop(gettextf("k = %d must be at least 1", k), domain = NA)
:
  the condition has length > 1 and only the first element will be used

Thank you.





--
View this message in context: http://r.789695.n4.nabble.com/k-nearest-neighbour-classification-tp4713523.html
Sent from the R help mailing list archive at Nabble.com.