问题
I have a question with regards to this post: cocktail party algorithm SVD implementation ... in one line of code?
I realize there are similar questions to this. However, please note that my particular question takes things in a new direction, inasmuch that I'm looking for a purely Python equivalent. Is this procedure as elegant/simple when written in Python 3.5 (as opposed to the original Octave 'one line of code')? Also include any relevant Python libraries for this kind of application. Of course, if it turns out that Python is not equipped for this kind of application at all, please explain why.
I'm just seeking some expert opinions about what it might look like and/or the feasibility in Python 3.5 only.
回答1:
How about using numpy? Using this guide I translated the statement to
from numpy import *
U, S, Vh = linalg.svd(dot((tile(sum(x*x,0),(x.shape[0],1))*x),x.T))
It runs but I do not have any data to actually test it.
来源：https://stackoverflow.com/questions/39465776/machine-learning-cocktail-party-audio-application