Haven't try to tune the parameters of the combined normal data though (dont
know why i forget that..)
I'll do that.
Thanks Andy
Regards,
Ady
On Wednesday, August 5, 2015, Andreas Mueller wrote:
> Do you have ground-truth? Then you should tune the parameters.
> Have you done that?
>
>
> On 08/04
Do you have ground-truth? Then you should tune the parameters.
Have you done that?
On 08/04/2015 01:45 PM, Ady Wahyudi Paundu wrote:
> Hi Andy, thank you for the swift reply.
>
> No, for both case I was using the same set of parameters (nu and gamma
> = 0.01, kernel=rbf)
>
> Thank you for your su
Hi Andy, thank you for the swift reply.
No, for both case I was using the same set of parameters (nu and gamma
= 0.01, kernel=rbf)
Thank you for your suggestion, I will look into it.
Regards,
Ady
On 8/5/15, Andreas Mueller wrote:
> Hi Ady.
> Are you selecting parameters separately for the two
Hi Ady.
Are you selecting parameters separately for the two models in the
separate case?
Btw, if you are modelling a single normal, maybe EllipticEnvelope would
work better.
Best,
Andy
On 08/04/2015 01:07 PM, Ady Wahyudi Paundu wrote:
> Hi all,
>
> How am I supposed to work with multiple set of
Hi all,
How am I supposed to work with multiple set of normal data for one-class SVM?
If I have two normal scenario data set, A and B for learning phase,
should I create predictor model separately (M(A) + M(B)) or can I
combine A and B to create just a single predictor model (M(A+B))?
I have try
