Message-ID: <BANLkTinFr1oc000zDHx-xMxsftD5dFO-vQ@mail.gmail.com>
Date: 2011-04-11T03:32:00Z
From: Steve Lianoglou
Subject: In svm(), how to connect quantitative prediction result to categorical result?
In-Reply-To: <8360A74801605D4487C1D39EF1FDE13502B5A5C4@EXCHANGEVS-03.ad.wsu.edu>
Hi Yunfei,
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?)
You have to figure out if you want the svm to do classification or regression.
If I remember correctly, a "vanilla" call to SVM will try to pick one
or the other in a "smart way" by looking at the types (and values) of
your labels (y vector).
You can be more explicit and tell the SVM what you want by specifying
a value for the `type` argument in your original `svm` call.
See ?svm for more info.
I'm not sure if I'm answering your question or not(?). If I didn't
understand what you wanted, perhaps you can rephrase your question, or
maybe explain how my answer is not what you were after ... otherwise
hopefully someone else can provide a better answer.
-steve
--
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