2013/10/8 Peter Prettenhofer <peter.prettenho...@gmail.com>: > that's a bug - I'll open a ticket for it. > A quick fix: call partial_fit instead of fit just before the ``for`` loop.
Peter, is this due to an optimization that turns coef_ into a Fortran-ordered array? If so, I don't think we need it any longer with NumPy 1.7 and the new sklearn.extmath.fast_dot: In [1]: X = np.random.randn(10000, 200) In [2]: Y = np.random.randn(200, 70) In [3]: %timeit np.dot(X, Y) 100 loops, best of 3: 16.5 ms per loop In [4]: Yf = asfortranarray(Y) In [5]: %timeit np.dot(X, Yf) 100 loops, best of 3: 16.7 ms per loop In [6]: numpy.__version__ Out[6]: '1.7.1' ------------------------------------------------------------------------------ October Webinars: Code for Performance Free Intel webinars can help you accelerate application performance. Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from the latest Intel processors and coprocessors. See abstracts and register > http://pubads.g.doubleclick.net/gampad/clk?id=60134071&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
