R help - Jul 2005 - Getting runtime error in stepclass

Hi!

I got the following runtime error when I tried to use svm method with
stepclass.

Error in "colnames<-"(`*tmp*`, value = c("0",
"1")) :
        attempt to set colnames on object with less than two dimensions

I repeated the same sequence of statements but this time I used the
classification function used in the example, i.e., "lda" and it worked
fine but I got the same error when I tried randomForest.

As the same script worked with a different classification function, I am
wondering if stepclass works with svm and randomForest.

I using R version 2.0.1 on a Linux machine. I am including the R script I
used below.

I would be grateful for any suggestion on how to make stepclass work with
these classification functions.

I would also like to make stepclass work with knn but knn does not have a
'predict' method, which is a requirement for a classification method to
work with stepclass. Is there any way to get around this?

Thanks,
Soma



library("e1071")
library("randomForest")
library("klaR")

td <- read.table("dgdata1.txt", header=TRUE, sep=",")
dgenes <- subset(td, dg == 1, select = dg:eg)
ndgenes <- subset(td, dg == 0, select = dg:eg)
n1 <- nrow(dgenes)
n2 <- nrow(ndgenes)
ndgrows <- 1:n2
selrows <- sample(ndgrows)
sndgenes <- ndgenes[selrows[1:n1],]

train <- rbind(dgenes, sndgenes)
attach(train)
traind <- subset(train, select = -dg)
trainr <- factor(dg)
detach(train)

sc_res <- stepclass(traind, trainr, "svm", direction =
"forward",
criterion = "AC", fold = 10)

Soma Saha wrote:
> Hi!
> 
> I got the following runtime error when I tried to use svm method with
> stepclass.
> 
> Error in "colnames<-"(`*tmp*`, value = c("0",
"1")) :
>         attempt to set colnames on object with less than two dimensions
> 
> I repeated the same sequence of statements but this time I used the
> classification function used in the example, i.e., "lda" and it
worked
> fine but I got the same error when I tried randomForest.
> 
> As the same script worked with a different classification function, I am
> wondering if stepclass works with svm and randomForest.
> 
> I using R version 2.0.1 on a Linux machine. I am including the R script I
> used below.
> 
> I would be grateful for any suggestion on how to make stepclass work with
> these classification functions.
> 
> I would also like to make stepclass work with knn but knn does not have a
> 'predict' method, which is a requirement for a classification
method to
> work with stepclass. Is there any way to get around this?
> 
> Thanks,
> Soma
> 
> 
> 
> library("e1071")
> library("randomForest")
> library("klaR")
> 
> td <- read.table("dgdata1.txt", header=TRUE,
sep=",")
> dgenes <- subset(td, dg == 1, select = dg:eg)
> ndgenes <- subset(td, dg == 0, select = dg:eg)
> n1 <- nrow(dgenes)
> n2 <- nrow(ndgenes)
> ndgrows <- 1:n2
> selrows <- sample(ndgrows)
> sndgenes <- ndgenes[selrows[1:n1],]
> 
> train <- rbind(dgenes, sndgenes)
> attach(train)
> traind <- subset(train, select = -dg)
> trainr <- factor(dg)
> detach(train)
> 
> sc_res <- stepclass(traind, trainr, "svm", direction =
"forward",
> criterion = "AC", fold = 10)
Looks like predict.svm does not always return "probabilities" in all 
cases, hence cannot be used in your case, I guess.
svmlight (interface in in packages klaR) will do, though. You also might 
want to use sknn() (also package klaR), since it has a predict method 
rather than knn().

For randomForest, we will enhance stepclass() to support it in future.

Uwe Ligges
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