I use Windows, R version 2.5.1
When I try to run stepclass (klaR) I get an error message/warning saying:
1: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar),
data = data, grouping = grouping, ...
Actually, I look 16 warnings of this type. Can anyone tell me what this
means?
Also, it returns only 2 out of the 79 variables as important, however these
variables don't make any biological sense... Might this be a problem of my
coding?
Here's some code and sample matrix:
>library(klaR)
>var <- read.table("C:\\Documents and Settings\\My
Documents\\silvia\\data\\variables.txt", header=T) ## matrix of 79 variables
>disp<- read.table("C:\\Documents and Settings\\My
Documents\\silvia\\data\\disperser.txt", header=T) ## vector defining my
groups
>disp<- as.factor(disp$disperser)
>data.step <- stepclass(var, disp, "lda", improvement = 0.05)
Sample matrix:
var:
P5.38 P6.45 P6.55 P6.63 P6.78 P6.87 P7.12 P7.42 P8.10 P8.88
P9.09 P9.30
P9.49 P9.55
0.00 11.08 3.16 0.76 0.40 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.64 0.00
0.00 0.00 0.00 0.00 0.00 1.63 0.00 6.89 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 4.78 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 131.56 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 5.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 16.00 9.59
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.88 0.48 0.89 0.00 0.00 0.00 0.00 0.16 0.00 0.00
0.00 0.00 0.21 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.75 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.41 20.62 8.13
8.87 8.27 12.51 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 133.24 0.00 0.73 0.00 0.00 0.00 0.00 1.34 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 1.32
0.00 1.81 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
7.26 8.16 1.50 0.00 0.00 0.00 1.97 1.28 0.00 0.00
0.00 1.16 0.00 0.00
0.00 1.48 0.22 0.00 0.00 0.00 0.00 0.00 1.80 0.66
0.47 0.47 0.75 0.00
0.00 1.34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 1.14 0.00
0.00 72.65 103.26 1.09 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.82 0.00 0.00 0.00 0.00 0.00 4.79 0.00 0.00 0.00
0.00 11.44 2.33 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.13 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.83 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 23.14 0.00 0.00 0.00 1.19 4.81 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 7.92 0.00 14.29 36.64 0.00 82.87 0.00 0.00
0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00
disp:
disperser
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
4
4
4
4
4
4
4
4
4
4
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