Hi everyone,
I submitted a pull request to enable grid_search with failing
classifiers. Did anyone have some time to look at it?
Thanks,
Michal
On 08/11/13 17:56, Michal Romaniuk wrote:
> Did anyone work on this problem (exceptions raised by classifiers in
> grid search) since? I would be happy
Hi Michal.
Thanks for wanting to work on this.
Could you please open an issue? That makes it easier to track the progress.
Could you also post the traceback / error from your example script there?
Thanks,
Andy
On 11/08/2013 09:56 AM, Michal Romaniuk wrote:
> Did anyone work on this problem (excep
Did anyone work on this problem (exceptions raised by classifiers in
grid search) since? I would be happy to do some work to fix this
problem, but would need some advice.
It seems to me like the easiest way around the issue is to wrap the call
to clf.fit() in a try statement and catch the exceptio
The error message could indeed be improved but this is a pathological
case anyway.
I would rather make the grid search fault tolerant instead of making
all the scikit-learn estimators accept invalid inputs (such as empty
dataset).
--
Olivier
http://twitter.com/ogrisel - http://github.com/ogrisel
Here is an example script:
import numpy
from sklearn import ensemble
y = numpy.random.random_integers(0,1,100)
X = numpy.zeros((100,0))
rf = ensemble.RandomForestClassifier()
rf.fit(X,y)
Michal
> I am not sure to understand. Please provide a minimalistic
> reproduction script (10 lines max) and
2013/6/20 Michal Romaniuk :
> What is the default behaviour for random forests with zero features? It
> seems to me that it just gives an error (although I'm not 100% sure if
> that's the cause). This is a problem when using a feature selection step
> and searching a grid for a good feature selecti
