oh sorry, I see now that you mention about evaluating. On Fri, 3 May 2019 at 10:12, Guillaume Lemaître <g.lemaitr...@gmail.com> wrote:
> You can always predict incrementally by predicting on batches of samples. > > On Fri, 3 May 2019 at 10:05, lampahome <pahome.c...@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. >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> > > > -- > 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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