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

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.

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


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