I am using 2-class SVM from
I have been recommended to calibrate the output of classifier.
In this regard, I found this page. The code works for me and I want to apply it in my project; however, I am not sure about the vector of
pred which its definition is "vector of predictions of each observation from the classifier. Should be real number."
The output of my classifier is like this:
Decision values: t34a t34b 0 0 attr(,"decision.values") 1/0 t34a -0.2859799 t34b -0.4527416 attr(,"probabilities") 1 0 t34a 0.17057557 0.8294244 t34b 0.07377427 0.9262257 Levels: 0 1
Do you know I should use which of this information for
pred? decision values? or probability values of target class, say class 1, i.e. first column of probability values?
Also, do you know how I should apply it in learning procedure? Typically, the learning procedure is as follows:
1) estimation of performance of SVM using Leave-One-Out cross-validation.
2) training SVM with whole training samples,
3) and then evaluating the model by testing samples.
If I want to use calibration technique, where I can do that?
I appreciated if you could help me.