Hi, Dear all,
I am just starting using R in my work and got some trouble to figure out some of the errors. Can anybody help me?
The following is the script:
read.csv('pupil.txt',header=TRUE,sep='\t')->pupil
samp<-c(1:50, 112:162, 171:220, 228:278)
pupil.nn2 <- nnet(Type ~ ., data = pupil, subset = samp, size = 2, rang = 0.1, decay = 5e-4, maxit = 200)
table(pupil$Type[-samp], predict(pupil.nn2, pupil[-samp,], type = "class"))
After running this, I got error information as
#Error in switch(type, raw = z, class = { :
# inappropriate fit for class
BTW, pupil.txt
X1 X2 Type
0.2 0.5 0
...........
..........
.........1
.........
.........
..........2
.......
........3
........
there are totally 351 records.
My objective is to classify them into 4 classes.
Thanks a lot for your help!
Help on NNET
2 messages · sbinny, Thomas W Blackwell
I'm not a nnet() user, but after reading the help, there are two things you might try, both in the model formula passed to nnet() in the third line of code below. Alternate version: pupil.nn2 <- nnet( as.factor(Type) ~ X1 + X2, ... (with all the remaining arguments as before). I'm not sure which (if either) of these two variants might do the trick. - tom blackwell - u michigan medical school - ann arbor -
On Thu, 17 Jul 2003, sbinny wrote:
The following is the script:
read.csv('pupil.txt',header=TRUE,sep='\t')->pupil
samp<-c(1:50, 112:162, 171:220, 228:278)
pupil.nn2 <- nnet(Type ~ ., data = pupil, subset = samp, size = 2, rang = 0.1, decay = 5e-4, maxit = 200)
table(pupil$Type[-samp], predict(pupil.nn2, pupil[-samp,], type = "class"))
There are totally 351 observations.
My objective is to classify them into 4 classes.
Thanks a lot for your help!