Manhattan, Cosine, Ln Form
\n# http:\/\/dataaspirant.com\/2015\/04\/11\/five-most-popular-similarity-measures-implementation-in-python\/<\/p>\n
# Manhattan
\ndef manhattan(x, y):
\nreturn sum( abs(a-b) for a, b in zip(x,y))<\/p>\n
d = manhattan([5,10], [30,20])
\nprint(d)<\/p>\n
#—— Cosine Distance
\nimport math
\ndef square_rooted(x):
\nreturn math.sqrt(sum([a * a for a in x]))<\/p>\n
def cosine_distance(x, y):
\nnumerator = sum ( a * b for a, b in zip(x, y ) )
\ndenominator = square_rooted(x) * square_rooted(y)
\nreturn numerator\/denominator
\nprint ( cosine_distance([3, 45, 7, 2], [2, 54, 13, 15]) )<\/p>\n
#—————-
\n#Ln Form Distance<\/p>\n
def ln_form_distance(x,y, dim):
\nreturn pow(sum([ pow(abs(a-b),dim) for a,b in zip(x,y)]), 1\/dim)<\/p>\n
print (ln_form_distance([3, 45, 7, 2], [2, 54, 13, 15], 3))<\/p>\n","protected":false},"excerpt":{"rendered":"
Manhattan, Cosine, Ln Form # http:\/\/dataaspirant.com\/2015\/04\/11\/five-most-popular-similarity-measures-implementation-in-python\/ # Manhattan def manhattan(x, y): return sum( abs(a-b) for a, b in zip(x,y)) d = manhattan([5,10], [30,20]) print(d) #—— Cosine Distance import math def square_rooted(x): return math.sqrt(sum([a * a for a in x])) def cosine_distance(x, y): numerator = sum ( a * b for a, b in zip(x, y … <\/p>\n