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 ? ? ? ?[[alternative HTML version deleted]]
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