Hello there, Is there any way to find matrix A for unknown data Xn using
estimated sources S?
for example if I use
1) ica_X = FastICA(n_components=xyz, algorithm='parallel',
whiten=True,fun='logcosh', fun_prime='', fun_args=None,
max_iter=1000,tol=0.0001, w_init=None, random_state=None)
2) ica_X.fit(X / X.std)
3) X_com = ica_X.transform(Xn / X.std)
So I think i am extracting sources ( as described in the ica.transform
module of scikitlearn)
My question, Is there any way to find mixing matrix for the new data using
existing estimated sources.
also I am little bit confused components and sources. when ica_X.components
is called what it gives? are these components or sources?
Any help will be highly appreciated.
Regards
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