[R] In svm(), how to connect quantitative prediction result to categorical result?
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Tue Apr 12 17:55:53 CEST 2011
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:
> looking at the fitted values
> 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?
> On Fri, Apr 8, 2011 at 8:35 PM, Li, Yunfei <yunfei_li at wsu.edu> wrote:
>> 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?)
>> 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
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