You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
In your code or function : "row_normalize()" as well as other functions, the shape of the function's input matrix should be the same in rows and columns. If the number of rows doesn't match up with that of its columns, we will get error from the function "np.dot()".
If the assumption is that "the matrix.shape[0] == matrix.shape[1]", then why bother to set:
m, n = self.A.shape ? It's really redundant and misleading.
I think that the code can be simplified.
The text was updated successfully, but these errors were encountered:
In your code or function : "row_normalize()" as well as other functions, the shape of the function's input matrix should be the same in rows and columns. If the number of rows doesn't match up with that of its columns, we will get error from the function "np.dot()".
If the assumption is that "the matrix.shape[0] == matrix.shape[1]", then why bother to set:
m, n = self.A.shape ? It's really redundant and misleading.
I think that the code can be simplified.
The text was updated successfully, but these errors were encountered: