[R] In svm(), how to connect quantitative prediction result to categorical result?

[Steve Lianoglou]

Hi,

On Tue, Apr 12, 2011 at 10:54 AM, Saeed Abu Nimeh <sabunime at gmail.com> wrote:
> I trained a linear svm and did classification. looking at the model I
> have, with a binary response 0/1, the decision values look like this:
> head(svm.model$decision.values)
> 2.5
> 3.1
> -1.0
>
> looking at the fitted values
> head(svm.model$fitted)
> 1
> 1
> 0
> So it looks like anything less than or equal 0 is mapped to the
> negative class, i.e. 0), otherwise it is mapped to the positive class,
> i.e. 1.

Yes -- so far, so good.

In SVM classification, when examples are predicted with a positive
decision value they are assigned to one class (lets say +1), and
examples with negative decision value are assigned to the other (-1).

Was there a remaining question, or?

-steve


>
>
>
> On Fri, Apr 8, 2011 at 8:35 PM, Li, Yunfei <yunfei_li at wsu.edu> wrote:
>> Hi,
>>
>> I am studying using SVM functions of e1071 package to do prediction, and I found during the training data are "factor" type, then svm.predict() can predict data directly by categories; but if response variables are "numerical", the predicted value from svm will be continuous quantitative numbers, then how can I connect these quantitative numbers to categories? (for example:in an example data set, the response variables are numerical and have two categories: 0 and 1, and the predicted value are continuous quantitative numbers from 0 to 1.3, how can I know which of them represent category 0 and which represent 1?)
>>
>> Best,
>>
>> Yunfei Li
>> --------------------------------------------------------------------------------------
>> Research Assistant
>> Department of Statistics &
>> School of Molecular Biosciences
>> Biotechnology Life Sciences Building 427
>> Washington State University
>> Pullman, WA 99164-7520
>> Phone: 509-339-5096
>> http://www.wsu.edu/~ye_lab/people.html
>>
>>
>>        [[alternative HTML version deleted]]
>>
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>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
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