2013/10/19 Andreas Mueller amuel...@ais.uni-bonn.de:
The multi-class documentation says
You don’t need to use these estimators unless you want to experiment
with different multiclass strategies:
all classifiers in scikit-learn support multiclass classification
out-of-the-box. Below is a
On 09/25/2013 05:31 AM, Lars Buitinck wrote:
2013/9/25 Luca Cerone luca.cer...@gmail.com:
I am sorry, but I went into the user documentation for logistic regression
and multiclass classification and didn't find any information about it
Hm, maybe we should put this in a more prominent place
Dear Olivier,
thanks for your reply.
On 25 September 2013 10:39, Olivier Grisel olivier.gri...@ensta.org wrote:
LogisticRegression is a already multiclass classifier by default using
the One vs Rest / All strategy by default (as implemented internally
by liblinear which LogisticRegression is
2013/9/25 Luca Cerone luca.cer...@gmail.com:
This morning I checked the source for LogisticRegression in
sklearn/linear_model/logistic.py and realized that by default it performs
multiclass classification
(this is not explained in the user guide
(this is not explained in the user guide
http://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
,
though).
All our classifiers support multiclass classification and this is
documented in various places.
I am sorry, but I went into the user documentation for
2013/9/25 Luca Cerone luca.cer...@gmail.com:
I am sorry, but I went into the user documentation for logistic regression
and multiclass classification and didn't find any information about it
Hm, maybe we should put this in a more prominent place like the
tutorial. I'll check the docs if I have
There are still a few things that are not clear to me from the
documentation. Can you customize the classifier to perform a different
decision function?
You can subclass it and override the decision_function method.
While true, this can be misleading. You're just changing the final
step used
2013/9/25 Luca Cerone luca.cer...@gmail.com:
(this is not explained in the user guide
http://scikit-learn.org/stable/modules/linear_model.html#logistic-regression,
though).
All our classifiers support multiclass classification and this is
documented in various places.
I am sorry, but
On 25 September 2013 13:55, Olivier Grisel olivier.gri...@ensta.org wrote:
2013/9/25 Luca Cerone luca.cer...@gmail.com:
(this is not explained in the user guide
http://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
,
though).
All our classifiers support
Dear all,
I am practising with scikit-learn to solve multiclass classification
problems.
As an exercise I am trying to build a model to predict the digits dataset
available with scikit-learn.
Ideally I would like to solve this using logistic regression, building a
predictor for each digit (one
Ok training a OneVsAll classifier it was actually easy.
To inspect the individual classifier I can use the .estimators_ attribute?
Do the estimators in it correspond to the .classes_ that is the
estimators_[0] is trained to recognize .classes_[0] vs the other and so on?
Is there a way to check
11 matches
Mail list logo
