https://github.com/scikit-learn/scikit-learn/pull/7177 makes silhouette more memory-efficient. Try that branch?
On 17 November 2017 at 05:46, Shiheng Duan <shid...@ucdavis.edu> wrote: > Hi Luigi, > > Actually my data has 621*1405 points and each point has 12 features. I > made it into a 2-D array and kmeans works well. The last time I ran it used > 64G RAM on a cluster. I don't know how much more RAM can I use. > > BTW, 1502 issue is about Orange. Is it the same with sklearn? > > Thanks. > > On Thu, Nov 16, 2017 at 1:14 AM, Luigi Lomasto <l.lomasto@ > innovationengineering.eu> wrote: > >> Hi Shiudan, >> >> You can try to see this link: https://github.com/biola >> b/orange3/issues/1502 >> >> You have 3D dimensional problem, right? For each feature you have 12 >> values, so probably your RAM is small. How much RAM has your pc? >> Let me know, >> >> Luigi >> >> >> Il giorno 16 nov 2017, alle ore 09:18, Shiheng Duan <shid...@ucdavis.edu> >> ha scritto: >> >> Hi all, >> >> I am doing cluster work and wanna use silhouette score to determine the >> number of clusters. But I got MemoryError when execute silhouette_samples. >> I searched it and found something related to numpy. But I cannot reproduce >> the numpy error. Is there any solution to it? >> >> The data is 621*1405*12. >> >> Thanks! >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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