Thanks. It does work now.
I also get another problem when I use naivebayes and prediction in myapplication
There was anerror message:
Error in table(predict(nb.obj, test.data[, subset, drop = FALSE]), test.data[, :
all arguments must have the same length
The length of test.data[,subset, drop=FALSE] and test.data[,ncol(expr.matrix)] of are the same. I further checked length ofpredict(nb.obj, test.data[, subset, drop = FALSE]) is 0. I do not know why.
The script is shown below. I also attached test data
evaluator- function(subset){
# k-fold cross validation
k- 5
splits- runif(nrow(expr.matrix))
results- sapply(1:k, function(i){
test.indx- (splits= (i-1)/k)
(splitsi/k)
train.indx- !test.indx
test.data- expr.matrix[test.indx, ,
drop=FALSE]
train.data- expr.matrix[train.indx, ,
drop=FALSE]
nb.obj- naiveBayes(train.data[,subset,
drop=FALSE], train.data[,ncol(expr.matrix)])
error.rate-
sum(predict(nb.obj,test.data[,subset, drop=FALSE]) ==
test.data[,ncol(expr.matrix)])/nrow(test.data)
return (error.rate)
})
print(subset)
print(mean(results))
return(mean(results))
}
subset- best.first.search(colnames(expr.matrix)[-ncol(expr.matrix)], evaluator)
Br,
Luffy
On 05/05/2012 12:53 PM, Petr Savicky wrote:
On Sat, May 05, 2012 at 09:21:10AM +0300, kiinalist wrote:
Hi,
I tried to use naivebayes in package 'e1071'.
when I use following parameter, only one predictor, there is an error.
m- naiveBayes(iris[,1], iris[,5])
table(predict(m, iris[,1]), iris[,5])
Error in log(sapply(attribs, function(v) { :
Non-numeric argument to mathematical function
However, when I use two predictors, there is not error any more.
m- naiveBayes(iris[,1:2], iris[,5])
table(predict(m, iris[,1:2]), iris[,5])
setosa versicolor virginica
setosa 49 0 0
versicolor 1 3719
virginica 0 1331
Hi.
A untested suggestion is to try
m- naiveBayes(iris[,1, drop=FALSE], iris[,5])
The difference is that iris[,1] is not a dataframe, while
both iris[,1:2] and iris[,1, drop=FALSE] are.
Hope this helps.
Petr Savicky.
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