Hi, On Tue, Apr 12, 2011 at 10:54 AM, Saeed Abu Nimeh <sabun...@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...@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]] >> >> ______________________________________________ >> R-help@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. >> > > ______________________________________________ > R-help@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 ______________________________________________ R-help@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.