> Why don't you use a kernel SVM (SVC)?
> There is no kernel Logistic Regression in sklearn. But there are some
> kernel-approximation
> methods that you could use together with various kernels and then use
> the standard LogisticRegression.
I don't know how to combine these methods, so I will hav
On Mon, Apr 29, 2013 at 10:53:21AM +0200, Andreas Mueller wrote:
> > You might try totally random trees embedding for this purpose:
> > http://scikit-learn.org/stable/modules/ensemble.html#totally-random-trees-embedding
> > and
> > http://scikit-learn.org/stable/auto_examples/ensemble/plot_random_f
>> So is there any method within scikit, that could help me finding a
>> feature mapping?
>
> I am not sure what you mean by feature mapping? Do you mean a non
> linear
> mapping to a feature spacing in which the classes should be
> separable?
Yes, sorry for being imprecise.
> You might try tot
On 04/28/2013 08:06 PM, Richard Cubek wrote:
> Hello everyone,
>
> 2) Playing around with LR, the results "look interesting"
> (https://dl.dropboxusercontent.com/u/95888530/logreg_1.png), but I was
> not able to reproduce a model adopting/"overfitting" to every single
> data point, as in the SVM ex
On 04/28/2013 11:19 PM, Gael Varoquaux wrote:
> On Sun, Apr 28, 2013 at 08:06:11PM +0200, Richard Cubek wrote:
>> how stable the python binding is regarding the website issue mentioned
>> above.
> Faily stable I would say. The remarks applied years ago.
>
>> So is there any method within scikit, th
On Sun, Apr 28, 2013 at 08:06:11PM +0200, Richard Cubek wrote:
> how stable the python binding is regarding the website issue mentioned
> above.
Faily stable I would say. The remarks applied years ago.
> So is there any method within scikit, that could help me finding a
> feature mapping?
I am n
Hello everyone,
I'm new to the list so first of all thanks a lot for your work on this
lib!
I need libsvm probability estimates as well as Logistic Regression (LR)
in a three classes problem with a training data set size of about 5-6000
at 20-50 features. I am familiar with python and octave (
