One way to encourage people to use the scorer API more would be to add a
more direct interface like:
def score(scoring, estimator, X, y=None, **kwargs):
return get_scorer(scoring)(estimator, X, y, **kwargs)
On 20 February 2015 at 20:58, Mathieu Blondel wrote:
>
>
> On Fri, Feb 20, 2015 at
On 21/02/15 23:20, Sturla Molden wrote:
> "I have discovered a truly marvelous proof, which this margin is too
> narrow to contain." ;-)
A more bizarre story...
Last time I said something like that was in 2004, when a postdoc, a
fellow PhD student and I had found some strange hexagonal patterns
"I have discovered a truly marvelous proof, which this margin is too
narrow to contain." ;-)
Sturla
On 21/02/15 22:58, Vlad Niculae wrote:
> Apologies in advance, but this fits so well, I couldn’t help myself.
>
> A Mathematician and an Engineer attend a lecture by a Physicist. The topic
> con
Apologies in advance, but this fits so well, I couldn’t help myself.
A Mathematician and an Engineer attend a lecture by a Physicist. The topic
concerns Kulza-Klein theories involving physical processes that occur in spaces
with dimensions of 9, 12 and even higher. The Mathematician is sitting,
On 20/02/15 18:34, Gael Varoquaux wrote:
> On Fri, Feb 20, 2015 at 05:27:12PM +0100, shalu jhanwar wrote:
>> i) Can I do it with more features (I have 16 features)?
>
> How do you visualize a 16-features space?
I think I know of a rather general solution to this problem. But I don't
think I shou
On 20/02/15 14:29, shalu jhanwar wrote:
> Hi guys,
>
> I am using SVM and Random forest classifiers from scikit learn. I wonder
> is it possible to plot the decision boundary of the model on my own
> training dataset so that I can have a feeling of the data? Is there any
> in-built example availabl
