Dear all,
I've sent a mail last week already. I've been trying to get this predict
function work, but somehow I keep on getting the same error. Read the help
files, searched the internet, but I don't seem to get what I'm doing wrong.
Anybody who has experience with this function? It's contained in the package
e1071.
Thank you in advance
On Thu, Feb 19, 2009 at 2:16 PM, joris meys <jorism...@gmail.com> wrote:
> Dear all,
>
> I tried a simple naive Bayes classification on an artificial dataset, but I
> have troubles getting the predict function to work with the type="class"
> specification. With type= "raw", it works perfectly, but with type="class" I
> get following error :
>
> Error in as.vector(x, mode) : invalid 'mode' argument
>
> Data : mixture.train is a training set with 100 points originating from 2
> multivariate gaussian distributions (class 0 and class 1), with X1 and X2 as
> coordinates in a 2-dimensional space. Mixture.test is a grid going from -15
> to +15 in both dimensions. Stupid data, but it's just to test.
>
> Code :
> Sigma <- matrix(c(10,3,3,2),2,2)
> mixture.train <- cbind(mvrnorm(n=50, c(0, 2), Sigma),rep(0,50))
> mixture.train <- as.data.frame(rbind(mixture.train,cbind(mvrnorm(n=50, c(2,
> 0), Sigma),rep(1,50))))
> names(mixture.train) <-c("X1","X2","Class")
> X1 <- rep(seq(-15,15,by=1),31)
> X2 <- rep(seq(-15,15,by=1),each = 31)
> mixture.test <- data.frame(X1,X2)
>
> Bayes.res <- naiveBayes(Class ~ X1 + X2, data=mixture.train)
> pred.bayes <-predict(Bayes.res, cbind(mixture.test$X1,
> mixture.test$X2),type="class")
>
> Tried it also with pred.bayes <-predict(Bayes.res,
> mixture.test,type="class"), but that gives the same effect. Is this a bug or
> am I missing something?
>
> Kind regards
> Joris Meys
> University Ghent
>
>
>
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