On 07/23/2012 11:49 AM, Peter Prettenhofer wrote:
> 2012/7/23 Emanuele Olivetti :
>> [..]
>>
>> As you can see the solution is very simple and just based on
>> np.logaddexp.reduce()
>> instead of np.exp().sum(), plus np.nan_to_num() and a little rearrangement.
>> I can prepare a pull request if yo
On 07/23/2012 11:38 AM, Gael Varoquaux wrote:
> Thanks a lot for your investigation work. It's very useful.
>
> On Mon, Jul 23, 2012 at 11:32:24AM +0200, Emanuele Olivetti wrote:
>> As you can see the solution is very simple and just based on
>> np.logaddexp.reduce() instead of np.exp().sum(), plus
2012/7/23 Emanuele Olivetti :
> [..]
>
> As you can see the solution is very simple and just based on
> np.logaddexp.reduce()
> instead of np.exp().sum(), plus np.nan_to_num() and a little rearrangement.
> I can prepare a pull request if you are interested.
Hi Emanuele,
Absolutely, that would be
Thanks a lot for your investigation work. It's very useful.
On Mon, Jul 23, 2012 at 11:32:24AM +0200, Emanuele Olivetti wrote:
> As you can see the solution is very simple and just based on
> np.logaddexp.reduce() instead of np.exp().sum(), plus np.nan_to_num()
> and a little rearrangement.
As fa
Hi,
During the weekend I was trying to play with GradientBoostingClassifier
and a dataset with a large number of classes. I observed an issue
during ".fit()", due to the MultinomialDeviance class code (sklearn v0.11):
/usr/lib/pymodules/python2.7/sklearn/ensemble/gradient_boosting.py:299:
Ru
