2012/9/7 Mathieu Blondel <[email protected]>:
> On my box, RidgeClassifier finishes in 136 seconds but kNN dies with
> MemoryError.
That's incredibly slow compared to all the other classifiers. Also
without --all_categories, it's slower than everything else.
I've already found out where things go wrong, though I still have no
idea why this didn't occur before.
Anyway, old-fashioned debugging with print statements points to line
103 of sklearn/linear_model/ridge.py as the culprit:
c = _solve(X * X.T + I, y, solver, tol)
(X * X.T) allocates a 90% dense (!) CSR matrix of size 11314**2.
That's close to a GB for the .data member alone and bigger than a
plain old np.array. Adding the diagonal matrix is enough the kill the
process (and all the PDF viewers I had open, stupid Linux
overcommit...).
> Could you try to identify which commit introduced the regression with git
> bisect?
I could try that, but I was actually working on something else when I
encountered this. I'm currently inclined to removing RidgeClassifier
from the example and opening an issue.
--
Lars Buitinck
Scientific programmer, ILPS
University of Amsterdam
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