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 automatically?
As I have to make several classification models it is not possible to give
class weight for every mode manually.
So I thought to give a try to oversampling or undersampling methods.
But from the answers it seems its not a best choice and make problem more
complicated.
So now I rephrase questions (may be I should make new question!!!!)--
How to chose class weight automatically in unbalanced classes data
classification?
Is it possible to do it via function GridSearchCV?
On Wed, Jul 25, 2012 at 5:33 PM, Jaques Grobler <[email protected]>wrote:
> 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 data for
> classification for example.
>
> Hope this helps.
> J
>
>
>
> 2012/7/25 Sheila the angel <[email protected]>
>
>> 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<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
>> <[email protected]>wrote:
>>
>>> @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 <[email protected]>
>>>
>>>> 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
>>>>
>>>>
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