Have you tried class_weight='auto'?
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May be this will clarify problem -
I have unbalanced class data in which I am performing SVM classification.
Classification with equal weight for both class gives very
low sensitivity etc. (misclassification of low data class).
I tried give different class weight but I am not sure how to do
it auto
Could you perhaps clarify what you would want to use this for?
AFAIK the scikit-learn doesn't explicitly implement those techniques but
perhaps it can be done
another way through some of the existing implementations, like useing
class_weights or re-calibration - if it has to do with imbalanced dat
yes that is what I am looking for
http://en.wikipedia.org/wiki/Oversampling_and_undersampling_in_data_analysis
Also in the reference http://nd.edu/~dial/papers/SPRINGER05.pdf (though I
haven't read it fully)
On Wed, Jul 25, 2012 at 4:16 PM, Jaques Grobler wrote:
> @Sheila
>
> Are you referring t
@Sheila
Are you referring to this type of thing?
http://en.wikipedia.org/wiki/Oversampling_and_undersampling_in_data_analysis
2012/7/25 Gael Varoquaux
> On Wed, Jul 25, 2012 at 02:13:41PM +0200, Sheila the angel wrote:
> >I would like to know are oversampling and undersampling methods
>
On Wed, Jul 25, 2012 at 02:13:41PM +0200, Sheila the angel wrote:
>I would like to know are oversampling and undersampling methods
>implemented in sklearn???
I don't know what you mean by oversampling and undersampling. Could you
detail.
Gael
-
Hi all,
I would like to know are oversampling and undersampling methods implemented
in sklearn???
Thank you
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Sheila
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