2010-12-23

HMF

More matrix factorization today. PCA is bad, HMF is good. Why is PCA bad? Because it does a good job at describing the variance of your data, which can have substantial contributions from—or be dominated by—noise. Why is HMF good? Because it models the noise-deconvolved underlying distribution.

2 comments:

  1. To sell this, you might want to say how "HMF" differs from factor analysis (e.g., as reviewed by Zoubin and Sam).

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  2. Good point. The only real difference is the objective function, which is annoying when it is changed from MSE to chi-squared.

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