[scikit-learn] Plot Cross-validated ROCs for multi-class classification problem

[Andreas Mueller]

Please stay on the mailing list.
There is no single roc curve for a 3 class problem. So what do you want 
to plot?

On 07/20/2018 10:40 AM, serafim loukas wrote:
> Hello Andy,
>
>
> Thank you for your response.
>
> What I want to do is to plot the average(mean) ROC across Folds for a 
> 3-class case.
> I have managed to do so for the binary case and I am trying to make it 
> work for the mutlti-class case but with no luck.
>
> There is an example in the documentation 
> (http://scikit-learn.org/stable/auto_examples/model_selection/plot_roc_crossval.html) 
> for the binary case.
> I want to do the same ( plot the mean ROC and the confidence interval 
> for my 3-class problem).
>
> Here is also my SO question about this: 
> https://stackoverflow.com/questions/51442818/average-roc-curve-across-folds-for-multi-class-classification-case-in-sklearn with 
> some code included.
>
>
>
> Best,
> Makis
>
>
>
>> On 20 Jul 2018, at 16:34, Andreas Mueller <t3kcit at gmail.com 
>> <mailto:t3kcit at gmail.com>> wrote:
>>
>> Hi Makis.
>> What do you mean by a roc curve for multi-class?
>> You can have one curve per class using OVR or one curve per pair of 
>> classes.
>> That doesn't need the OneVsRestClassifier, it's more a matter of 
>> evaluation.
>>
>> Cheers,
>> Andy
>>
>> On 07/20/2018 05:35 AM, serafim loukas wrote:
>>> Dear Scikit-learn community,
>>>
>>>
>>> I have a 3 class classification problem and I would like to plot the 
>>> average ROC across Folds.
>>> There is an example in scikit-learn website but only for binary 
>>> classification problems 
>>> (http://scikit-learn.org/stable/auto_examples/model_selection/plot_roc_crossval.html).
>>>
>>> I want to do the same but in the case of 3 classes. I have tried to 
>>> use `clf = OneVsRestClassifier(LinearDiscriminantAnalysis())`but I 
>>> am having a hard time to make it work.
>>>
>>>
>>> Any help would be appreciated,
>>> Makis
>>>
>>>
>>> _______________________________________________
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>>
>

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