n similar results.
HTH,
Michael
Thank you,
From: Pagliari, Roberto
[mailto:rpagli...@appcomsci.com<mailto:rpagli...@appcomsci.com>]
Sent: Tuesday, October 21, 2014 9:39 AM
To:
scikit-learn-general@lists.sourceforge.net<mailto:scikit-learn-general@lists.sourceforge.net>
Subject: Re: [S
al stability and results with LibLinear
> (LinearSVM) are satisfactory, then you should try using
> `sklearn.svm.SVC(kernel="linear")` and check if you obtain similar results.
>
> HTH,
> Michael
>
>
>>
>>
>> Thank you,
>>
>>
>>
>
;
>
> I will try tuning gamma but, again, with quantization it seems to be
> working just fine.
>
>
>
> Thanks,
>
>
>
> *From:* Michael Eickenberg [mailto:michael.eickenb...@gmail.com
> ]
> *Sent:* Tuesday, October 21, 2014 9:32 AM
> *To:* scikit-learn-gen
Hi, Roberto
> Does anyone know if rbf is constrained in terms of number of dimensions?
No, there is no constraint on the number of dimensions
> I sometimes get weird results with SVM and rbf kernel in terms of false
> positive/negative rates.
Maybe you are overfitting or the data is just not
that many
samples (for example, numerical issues)?
Thank you,
From: Pagliari, Roberto [mailto:rpagli...@appcomsci.com]
Sent: Tuesday, October 21, 2014 9:39 AM
To: scikit-learn-general@lists.sourceforge.net
Subject: Re: [Scikit-learn-general] SVM with rbf kernel
Hi,
I was asking if having lot of
...@gmail.com]
Sent: Tuesday, October 21, 2014 9:32 AM
To: scikit-learn-general@lists.sourceforge.net
Subject: Re: [Scikit-learn-general] SVM with rbf kernel
Dear Roberto,
On Tue, Oct 21, 2014 at 2:58 PM, Pagliari, Roberto
mailto:rpagli...@appcomsci.com>> wrote:
I sometimes get weird results wi
Dear Roberto,
On Tue, Oct 21, 2014 at 2:58 PM, Pagliari, Roberto
wrote:
> I sometimes get weird results with SVM and rbf kernel in terms of false
> positive/negative rates.
>
>
>
> I suspect there may be numerical issues going on, because I’m not seeing
> the same issues with linearSVC.
>
>
>
T
