FA gets used a lot in finance for getting tractable factorizations of large
covariance matrices. Definitely would be very useful to have in sklearn.
On Wed, Jan 18, 2012 at 5:56 PM, David Warde-Farley <
[email protected]> wrote:
> On Wed, Jan 18, 2012 at 11:49:07PM +0100, Andreas wrote:
> > > Actually, I am not sure what FA means. For me ICA, PCA, or any
> > > decomposition model is an FA. Joris, what do you have in mind in
> > > particular?
> > >
> > >
> > Factor analysis is a decomposition with a particular
> > assumption about the noise.
>
> tl;dr (probabilistic) PCA assumes isotropic Gaussian noise, factor analysis
> relaxes this to diagonal.
>
> It has identifiability problems though -- the latent factors are only
> unique
> up to a rotation.
>
>
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