[scikit-learn] Can I evaluate clustering efficiency incrementally?

[Guillaume Lemaître]

oh sorry, I see now that you mention about evaluating.

On Fri, 3 May 2019 at 10:12, Guillaume Lemaître <g.lemaitre58 at gmail.com>
wrote:

> You can always predict incrementally by predicting on batches of samples.
>
> On Fri, 3 May 2019 at 10:05, lampahome <pahome.chen at mirlab.org> wrote:
>
>> I see some algo can cluster incrementally if dataset is too huge ex:
>> minibatchkmeans and Birch.
>>
>> But is there any way to evaluate incrementally?
>>
>> I found silhouette-coefficient and Calinski-Harabaz index because I don't
>> know the ground truth labels.
>> But they can't evaluate incrementally.
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>
>
> --
> Guillaume Lemaitre
> INRIA Saclay - Parietal team
> Center for Data Science Paris-Saclay
> https://glemaitre.github.io/
>


-- 
Guillaume Lemaitre
INRIA Saclay - Parietal team
Center for Data Science Paris-Saclay
https://glemaitre.github.io/
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