Hi Steve,

No custom kernel. (This is the exact same data that I call svm with.  
svm works without a complaint.)

traindata is just a dataframe of numerical attributes
trainlabels is just a vector of labels. ("good", "bad")

Then I call

model <- rvm(x,y)




On 8/19/09 11:50 AM, Steve Lianoglou wrote:
> Hi,
>
> On Aug 19, 2009, at 1:27 PM, Noah Silverman wrote:
>
>> Hello,
>>
>> In my ongoing quest to develop a "best" model, I'm testing various 
>> forms of SVM to see which is best for my application.
>>
>> I have been using the SVM from the e1071 library without problem for 
>> several weeks.
>>
>> Now, I'm interested in RVM and LSSVM to see if I get better performance.
>>
>> When running RVM or LSSVM on the exact same data as the SVM{e1071}, I 
>> get an error that I don't understand:
>>
>> Error in .local(x, ...) : kernel must inherit from class 'kernel'
>>
>> Does this make sense to anyone?  Can you suggest how to resolve this?
>
> Sure, it just means that whatever you are passing as a value to the 
> kernel= parameter of your function call is not a kernel function (that 
> kernlab knows about).
>
> Did you rig up a custom kernel function? If so -- be sure to set its 
> class properly. Otherwise, can you provide something of a 
> self-contained piece of code that you're using to invoke these 
> functions such that it's giving you these errors?
>
> -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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