[R] Can't see what i did wrong..

Sarah Goslee sarah.goslee at gmail.com
Thu Nov 15 16:47:47 CET 2012


Hi Jessica,

Talking may help you, but it's kind of a waste of time for the
thousands of readers of R-help unless you provide a reproducible
example and full context. We'd like to help, but can't without
adequate information.

Sarah

On Thu, Nov 15, 2012 at 9:48 AM, Jessica Streicher
<j.streicher at micromata.de> wrote:
> Now i let it run for one specific set and got the same bad result, then i deactivated the probabilities and got a good result, then i activated the probabilities again and got a good result .. huh???
>
> On 15.11.2012, at 15:32, Jessica Streicher wrote:
>
>> Its not scaling.. so..
>>
>> I guess i'll stay severely frustrated, and yes i know this is probably not enough information for anyone to help.
>> Still, talking helps ;)
>>
>> On 15.11.2012, at 15:15, Jessica Streicher wrote:
>>
>>> with
>>>
>>> pred.pca<-predict(splits[[i]]$pca,trainingData at samples)[,1:nPCs]
>>> dframe<-as.data.frame(cbind(pred.pca,class=isExplosive(trainingData,2)));
>>> results[[i]]$classifier<-ksvm(class~.,data=dframe,scaled=T,kernel="polydot",type="C-svc",
>>>              C=C,kpar=list(degree=degree,scale=scale,offset=offset),prob.model=T)
>>>
>>> and a degree of 5 i get an error of 0 reported by the ksvm object. But when doing
>>>
>>> pred.pca<-predict(splits[[i]]$pca,trainingData at samples)[,1:nPCs]
>>> pred.svm<-kernlab::predict(results[[i]]$classifier,pred.pca,type="probabilities");
>>> results[[i]]$trainResults$predicted<-pred.svm[,2]
>>>
>>> the results vary widely from the class vector. Nearly all predictions are somewhat around 0.29. Its just strange. And i have no idea where things go wrong. They're in the same loop with i, so its probably not an indexing issue.
>>>
>>> Maybe kernlabs predict doesn't scale the data or something?
>>>
>>


--
Sarah Goslee
http://www.functionaldiversity.org




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