def get_distance ( F , x ) : n = x . shape [ 0 ] square = F . sum ( x ** 2.0 , axis = 1 , keepdims = True ) distance_square = square + square . transpose ( ) - ( 2.0 * F . dot ( x , x . transpose ( ) ) ) # Adding identity to make sqrt work. return F . sqrt ( distance_square + F . array ( np . identity ( n ) ) )
how to specify distance metric for k means in python
Helper function for margin - based loss . Return a distance matrix given a matrix .
def get_distance(F, x):
    """Helper function for margin-based loss. Return a distance matrix given a matrix."""
    n = x.shape[0]

    square = F.sum(x ** 2.0, axis=1, keepdims=True)
    distance_square = square + square.transpose() - (2.0 * F.dot(x, x.transpose()))

    # Adding identity to make sqrt work.
    return F.sqrt(distance_square + F.array(np.identity(n)))