Dear Hamed,
Can you share the code of "balanced accuracy" as you mentioned in last mail.
On Tue, Jul 29, 2014 at 12:07 AM, Hamed Zamani <[email protected]> wrote:
> Dear Mario,
>
> Yes of course. Sorry I forgot to mention GMeans. It is also one of the
> measures which have been used frequently.
>
> -- Hamed
>
>
>
> On Tue, Jul 29, 2014 at 2:24 AM, Mario Michael Krell <[email protected]>
> wrote:
>
>> Dear Hamed,
>>
>> I think it would be a good idea to also consider gmean when extending
>> scikit. It is the geometric mean of TNR and TPR instead of the arithmetic
>> mean used for the balanced accuracy.
>>
>> Greets
>>
>> Mario
>>
>> On 28.07.2014, at 19:00,
>> [email protected] wrote:
>>
>> Dear Joel,
>>
>> Sorry for the delay. I was in a trip and I couldn't check my email.
>>
>> To the best of my knowledge and according to the kind responses in this
>> email thread, we cannot claim that an specific measure is better than the
>> others for imbalanced data. In other words, there are some evaluation
>> measure suitable for imbalanced data and each of them has its own
>> advantages. Hence, choosing the best evaluation measure totally depends on
>> the application which you are working on.
>>
>> Anyway, "Matthew's Correlation Coefficient", "AUC of ROC", "F-measure",
>> "Balanced Accuracy", and generally "Weighted Accuracy" have been used
>> frequently in the literature. Among these measures, only "balanced
>> accuracy" is not developed in scikit-learn and I think it is worthwhile to
>> add it to this library. I have developed it before and if you want I can
>> add it to the project or send it to you.
>>
>> Kind Regards,
>> Hamed
>>
>>
>>
>>
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>
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--
Warm Regards
Yogesh Karpate
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