[R] svm and RMSE

[Uwe Ligges]

On 19.02.2010 01:29, Amy Hessen wrote:
>
> Hi
> Thank you very much for your reply.
>
> I meant I got different RMSE with different runs to the same program without any change for the dataset or the parameters of SVM.
>
> This is my code:
>
> library(e1071)
> readingmydata<- as.matrix(read.delim("mydataset.txt"))
> train.x<- readingmydata[,-1]
> train.y<- readingmydata[,1]
>
> mymodel<- svm(train.x, train.y, cross=10)
> summary(mymodel)
 >
> can you please tell me how I can fix that error?

No error at all, it is expected: You get different partitions of the 
data for cross validation since they are samples "at random". If you 
want to get the exactly same results, use a seed for the random number 
generator such as:

set.seed(123)
mymodel<- svm(train.x, train.y, cross=10)
summary(mymodel)

Uwe Ligges



> Cheers,
> Amy
>
>
>> Date: Tue, 16 Feb 2010 10:33:19 -0500
>> Subject: Re: [R] svm and RMSE
>> From: mailinglist.honeypot at gmail.com
>> To: amy_4_5_84 at hotmail.com
>> CC: r-help at r-project.org
>>
>> Hi,
>>
>> On Fri, Feb 12, 2010 at 3:00 PM, Amy Hessen<amy_4_5_84 at hotmail.com>  wrote:
>>>
>>> Hi,
>>> Every time I run a svm regression program, I got different RMSE value.
>>> Could you please tell me what the reason for that?
>>
>> Sorry, your question is a bit vague.
>>
>> Can you provide an example/code that shows this behavior? Is the
>> different RMSE over different folds of cross validation. Over the same
>> data? With the same parameters? Is the RMSE significantly different?
>>
>> Providing an example that shows this behavior would help.
>>
>> Thanks,
>> -steve
>>
>> --
>> Steve Lianoglou
>> Graduate Student: Computational Systems Biology
>> | Memorial Sloan-Kettering Cancer Center
>> | Weill Medical College of Cornell University
>> Contact Info: http://cbio.mskcc.org/~lianos/contact
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