Thanks Daniel.
On Tue, Jul 23, 2013 at 2:40 AM, Daniel Vainsencher <
daniel.vainsenc...@gmail.com> wrote:
> I opened the issue for the first, also mentioning the second problem.
>
> https://github.com/scikit-learn/scikit-learn/issues/2191
>
> Daniel
>
>
> On 07/22/2013 03:16 PM, Andreas Mueller
I opened the issue for the first, also
mentioning the second problem.
https://github.com/scikit-learn/scikit-learn/issues/2191
Daniel
On 07/22/2013 03:16 PM, Andreas Mueller wrote:
On 07/22/2013 02:12 PM, Anne Dwyer wrote:
On 07/22/2013 02:12 PM, Anne Dwyer wrote:
> Andy,
>
> Shouldn't we also pull a ticket because using a uniform weight
> distribution does not give the same results as running the SVM without
> weights? (See my original post on the problem.)
I think that should scale the C.
If it doesn't, please al
Andy,
Shouldn't we also pull a ticket because using a uniform weight distribution
does not give the same results as running the SVM without weights? (See my
original post on the problem.)
Thanks,
Anne
On Mon, Jul 22, 2013 at 4:50 AM, Andreas Mueller
wrote:
> Hi Daniel.
> Could you please ope
Hi Daniel.
Could you please open an issue and maybe provide a sample script that
demonstrates that
changing the sample weights doesn't change the decision function?
That sounds like a bug.
Cheers,
Andy
On 07/21/2013 02:08 PM, Daniel Vainsencher wrote:
I encountered similar problems.
Weightin
I encountered similar problems.
Weighting libsvm inputs under sklearn seems unsafe at any speed...
Amusingly enough, I think the pretty demo at [1] demonstrates the
problem. Notice how the white samples are really dominant... but the
decision boundary is consistent with uniform weights.
If you ch
Peter,
I tried your suggestion. But my training error with sample weights is still
not the same as without sample weights. It seems like I am missing
something here. It doesn't seem to work for me.
Anne Dwyer
On Fri, Jul 12, 2013 at 5:19 PM, Peter Prettenhofer <
peter.prettenho...@gmail.com> wr
try float(len(y_train)) - seems like C default is int...
Am 13.07.2013 00:10 schrieb "Anne Dwyer" :
> Peter,
>
> Thanks for your answers. When I scale C by len(y_train), I get the
> following error:
>
> ValueError: C <= 0
>
> Anne Dwyer
>
>
> On Fri, Jul 12, 2013 at 3:34 PM, Peter Prettenhofer <
>
Peter,
Thanks for your answers. When I scale C by len(y_train), I get the
following error:
ValueError: C <= 0
Anne Dwyer
On Fri, Jul 12, 2013 at 3:34 PM, Peter Prettenhofer <
peter.prettenho...@gmail.com> wrote:
> Hi Anne,
>
> I would also expect that using uniform weights should result in th
2013/7/12 Peter Prettenhofer
> Hi Anne,
>
> I would also expect that using uniform weights should result in the same
> solution as no weights -- but maybe there is an interaction with the C
> parameter... for this we would need to know more about the internals of
> libsvm and how it handles sampl
Hi Anne,
I would also expect that using uniform weights should result in the same
solution as no weights -- but maybe there is an interaction with the C
parameter... for this we would need to know more about the internals of
libsvm and how it handles sample weights - try scaling C by
``len(y_train
I have been using the sonar data set (I believe this is a sample data set
used in many demonstrations of machine learning.) It is a two class data
set with 60 features with 208 training examples.
I have a questions about using sample weights in fitting the SVM model.
When I fit the model using sc
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