Hi Nitin,
It can be solved by splitting your data a bit different. You need more
training data than you have evaluation data, eg :
i1 = 1:400
i2=401:d
Then it works on my computer. No clue as to where the error originates from
though.
Cheers
Joris
On Tue, Jun 1, 2010 at 4:27 PM, Nitin niti...@gmail.com wrote:
Dear All,
I'm getting a error while trying to apply the BreastCancer dataset
(package=mlbench) to kknn (package=kknn) that I don't understand as I'm new
to R.
The codes are as follow:
rm = (list = ls())
library(mlbench)
data(BreastCancer)
library(kknn)
BCancer = na.omit(BreastCancer)
d = dim(BCancer)[1]
i1 = seq(1, d, 2)
i2 = seq(2, d, 2)
t1 = BCancer[i1, ]
t2 = BCancer[i2, ]
y2 = BCancer[i2, 11]
x = 10
k = array(1:x, dim = c(x,1))
ker = array(c( rectangular, triangular, epanechnikov, biweight,
triweight, cos, inv, gaussian), dim = c(8,1))
f = function(x, ker){
BreastCancer.kknn - kknn(Class~., train = t1, test = t2, k = x,
kernel = ker, distance = 1)
fit = fitted(BreastCancer.kknn)
z - (fit==y2)
z.e - (100 - (length(y2)-length(z[!z]))/length(y2)*100 )
}
err.k = function(ker){
error.BreastCancer = apply(k,1,function(y) f(y, ker))
}
err.ker = apply(ker, 1, err.k)
colnames(err.ker) = c(rectangular, triangular, epanechnikov,
biweight,
triweight, cos, inv, gaussian)
print(err.ker)
It throws a error: Error in as.matrix(learn[, ind == i]) :
(subscript) logical subscript too long
In addition: Warning messages:
1: In model.matrix.default(mt, mf) : variable 'Id' converted to a factor
2: In model.matrix.default(mt, test) : variable 'Id' converted to a factor
I tried the codes with other datasets in mlbench package and most of them
working. That is the mistake here for this particular dataset and how can I
solve it?
Thanks
Nitin
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--
Joris Meys
Statistical Consultant
Ghent University
Faculty of Bioscience Engineering
Department of Applied mathematics, biometrics and process control
Coupure Links 653
B-9000 Gent
tel : +32 9 264 59 87
joris.m...@ugent.be
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