[R] naiveBayes other than e1071
Uwe Ligges
ligges at statistik.uni-dortmund.de
Tue Jun 5 21:56:28 CEST 2007
Saeed Abu Nimeh wrote:
> Max,
> Thanks. I have tried it but i keep getting an error:
> Error in as.vector(x, mode) : invalid argument 'mode'
> Do I have to do something specific when using the class column. I tried
> both y.y<-as.vector and y.y<-as.factor.
>
> dread<-read.table('dataset.csv',sep=",")
> x.x<-as.matrix(dread[,2:256])
> y.y<-as.vector(dread[,1])
> nb<- NaiveBayes(x=x.x,grouping=y.y)
> pred.nb<-predict(nb)
>
> Error in as.vector(x, mode) : invalid argument 'mode'
Please tell us (according to the posting guide): Which version of R?
Which version of klaR? Example data that reproduce the error?
Uwe Ligges
> Thanks,
> Saeed
>
> Kuhn, Max wrote:
>> Saeed,
>>
>> There is a version in the klaR package. I recently submitted a change to
>> the predict function that may be related to your problem.
>>
>> If:
>>
>> 1. the posterior probabilities (apart from the prior) are being
>> approximated by the product of the p(x_i|y_j) and
>>
>> 2. a lot of predictors are being used
>>
>> then posterior probabilities may have values of absolute zero.
>>
>> When the approximation is used, the approximate posterior probabilities
>> are normalized by their sum (which is zero in such cases).
>>
>> The patch in klaR uses the product of the conditional divided by the
>> marginal of x_i (per the true formula). I haven't seen the problem occur
>> with this patch.
>>
>> HTH,
>>
>> Max
>>
>> -----Original Message-----
>> From: r-help-bounces at stat.math.ethz.ch
>> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Saeed Abu Nimeh
>> Sent: Monday, June 04, 2007 2:45 PM
>> To: r-help at stat.math.ethz.ch
>> Subject: [R] naiveBayes other than e1071
>>
>> Hi List,
>> Is there a naiveBayes interface other than the one in e1071 package. For
>> some reason on certain datasets all predicted values are NaN, but it
>> predicts well on others.
>> Thanks,
>> Saeed
>> ---
>> model <- naiveBayes(x.train, y.train, laplace = 3)
>> pred <- predict(model,x.test,type="raw")
>>
>> ______________________________________________
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>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
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>
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