Hi Bertrand,
I am not familiar with RandomizedPCA so I do not known if nipals is faster
than RandomizedPCA. It is for sure faster than SVD when we are interested
only in few components. My impression is that RandomizedPCA is an
approximation of PCA while nipals should be an algorithm that theoreti
We've confirmed it was an MKL threading deadlock:
https://github.com/joblib/joblib/issues/138#issuecomment-44682214
Cheers,
f
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Hello,
Indeed, SVM methods only work with positive definite kernels (as all kernel
methods in Machine Learning). This is because you can view pd kernel as
inner product, which you can't if the kernel isn't pd. Kernel methods
(including SVM) "only" replace inner products with kernels, thus mapping
t
2014-05-30 22:34 GMT+02:00 Anders Aagaard :
> Which blas implementation are you using? openblas is known to cause this
> issue.
Same thought here, but this time it's MKL.
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Which blas implementation are you using? openblas is known to cause this issue.
On Wed, May 28, 2014 at 7:51 AM, Ronnie Ghose wrote:
> hmm this is going to be annoying, but have you debugged it at all e.g. have
> you tried seeing if you can find where it is at when it hits that 0 cpu? /
> try pri
