SVD on the Netflix matrix (Part 2)

About a week ago, we saw some basic performance stats on computing the SVD of the netflix matrix using Matlab‘s internal routines and the Propack software.

One of the comments suggested trying ipython, scipy, and numpy. So we did!

netflix_svd.py is up on the gist. Please see the previous post for more detail on what this is doing.

Thanks to Yangyang Hou for running these so quickly! In this case, we found that propack returned the correct singular values. Not sure what is going on with the matlab interface there!

# PROPACK
k    seconds
10   36.9860050678
25   78.114607811
50  150.511465788
100 328.731420994
150 500.544333935
200 719.040390968

# ARPACK (A^T A)
k    seconds
10 51.504776001
25 103.392450094
50 182.359881163
100 436.23743701
150 590.644889116
200 821.440295219

# SVDLIBC
k    seconds
10 74.2832891941
25 134.539175034
50 235.082634926
100 477.956938028
150 732.327076912
200 988.136811972
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One Response to SVD on the Netflix matrix (Part 2)

  1. Pingback: SVD on the Netflix matrix | David Gleich: a notebook

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