category.
> > I also tried downloading the 0.13 version from source and installing it.
This
> > time I see a different error. The steps to reproduce for version 0.13 in
ipython
> > are as follows:
> You can not necessarily load a classifier that was trained with one
> version in another version.
>> That would be great.
>> Which version of sklearn are you using?
> I am on scikit 0.12.1
>
>> Also, are you aware that you don't need the OneVsRestClassifier for
>> multi-class support in SGDClassifier?
>> SGDClassifier has multi-class support on its own.
>> If you didn't know this, it would be
In your code, 'document' is just a string, not a feature vector. You should
use the same Vectorizer that you used to train the classifier to begin with.
Trained classifier objects are generally not compatible across versions.
You should retrain the classifier using the new version (and who knows,
> Could you please provide a minimum code sample to reproduce and open an
> issue on github.
Following the minimalistic code to reproduce the issue (assuming the
classifier is already trained and saved). I will open the issue on github for
the same.
Hi Ark
Thanks for reporting the issue.
Could you please provide a minimum code sample to reproduce and open an
issue on github.
That would be great.
Which version of sklearn are you using?
Also, are you aware that you don't need the OneVsRestClassifier for
multi-class support in SGDClassifier?
S
Hello,
I see an issue with predict in case of predicting a text document. [I load
an already trained classifier (OneVsRest(SGDClassifier(loss=log))) using
joblib.load].
Thanks.
In [1]: import sklearn
In [2]: from sklearn.externals import joblib
In [4]: clf = joblib.load("classifier.joblib
