Hello,
I'm trying to follow the spectral clustering
example<http://scikit-learn.org/stable/auto_examples/cluster/plot_segmentation_toy.html>
and
am not very skilled in machine learning. From reading about normalized
cuts, I understand most of what is going on, but am confused particularly
in this line of the example:
graph
<http://docs.scipy.org/doc/scipy-0.11.0/reference/generated/scipy.sparse.coo_matrix.getH.html#scipy.sparse.coo_matrix>.data
= np.exp(-graph
<http://docs.scipy.org/doc/scipy-0.11.0/reference/generated/scipy.sparse.coo_matrix.getH.html#scipy.sparse.coo_matrix>.data
/ graph
<http://docs.scipy.org/doc/scipy-0.11.0/reference/generated/scipy.sparse.coo_matrix.getH.html#scipy.sparse.coo_matrix>.data.std())
Can someone offer an explanation of what this step is doing for a novice?
It would be greatly appreciated, thanks!
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