Hi Safi,
On Sun, Sep 8, 2013 at 1:58 PM, Safi Ullah Marwat
<safiullahmar...@gmail.com<mailto:safiullahmar...@gmail.com>> wrote:
Thank you Gael,
I actually want to know the distance between the entries of existing mixing
matrix and the newly calculated ones (the questioned thing)
As Gael you compute your `A` only once. If you want to compute distances you
might want to refit ICA on Xn and compare the old with the new `components`
using some sort of distance metric or r2 on the flattened arrays.
The more important question, however, seems to be why you would want to do that?
If Xn and X are from the same data it might be better to draw ,e.g., random,
samples from the entire X's range for best distribution estimates rather than
fitting on parts of X.
Since ICA is not a probabilistic model is non-convex and cannot be computed in
closed form, it does not come with a `natural` score and solutions may vary
significantly, depending on random state..
Determining the appropriateness of ICA is definitely subject-matter specific.
Depending on your use case you might want to fit several ICA solutions (while
keeping random_state floating) and pick the best solution, where `best` is
defined by your custom criterion.
HTH,
Denis
Thanks
On Sun, Sep 8, 2013 at 2:18 PM, Gael Varoquaux
<gael.varoqu...@normalesup.org<mailto:gael.varoqu...@normalesup.org>> wrote:
On Sun, Sep 08, 2013 at 01:40:49AM +0500, Safi Ullah Marwat wrote:
> My question, Is there any way to find mixing matrix for the new data using
> existing estimated sources.
The mixing matrix is computed once and for all, you are not recomuting a
mixing matrix given new data but existing estimated sources, as in a
'transform'.
> also I am little bit confused components and sources. when
> ica_X.components is called what it gives? are these components or
> sources?
In ICA language, these would be an unmixing matrix, in other words,
components on which you project to find sources. You can check out the
source code of the transform method to see exactly how that happens.
HTH,
Gaël
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