python - sklearn cosine similarity :: AttributeError: 'module' object has no attribute 'metrics' - 


ur[5][8]= [[0,3,4,0,0,0,5,0], [4,5,0,0,0,0,3,0], [0,4,0,3,0,0,1,4], [2,0,5,0,0,0,3,0], [0,0,0,5,0,0,0,4]]

0 means movie not rated want predict rating of unrated movie of each user using cosine similarity , after calculating similarity pick k similar user , predict according that

but how calculate cosine similarity using inbuilt function in skearn library or other

code: similar=[[0] * 5 in range(5)] print similar x in range(0,5):     y in range(0,5):         similar[x][y] = sklearn.metrics.pairwise.cosine_similarity(ur[x],ur[y])  error : runfile('c:/users/nitin/cf/first.py', wdir='c:/users/nitin/cf') [[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]] traceback (most recent call last):    file "<ipython-input-18-e55296403aad>", line 1, in <module>     runfile('c:/users/nitin/cf/first.py', wdir='c:/users/nitin/cf')    file "c:\users\nitin\anaconda2\lib\site-packages\spyder\utils\site\sitecustomize.py", line 880, in runfile     execfile(filename, namespace)    file "c:\users\nitin\anaconda2\lib\site-packages\spyder\utils\site\sitecustomize.py", line 87, in execfile     exec(compile(scripttext, filename, 'exec'), glob, loc)    file "c:/users/nitin/cf/first.py", line 23, in <module>     similar[x][y] = sklearn.metrics.pairwise.cosine_similarity(ur[x],ur[y])  attributeerror: 'module' object has no attribute 'metrics'

what pass in cosine_similarity or how correctly

you need import module use it.

from sklearn.metrics.pairwise import cosine_similarity

or

import sklearn # use  sklearn.metrics.pairwise.cosine_similarity(ur[x],ur[y])

then use it.

from sklearn.metrics.pairwise import cosine_similarity  ur = [[0,3,4,0,0,0,5,0], [4,5,0,0,0,0,3,0], [0,4,0,3,0,0,1,4], [2,0,5,0,0,0,3,0], [0,0,0,5,0,0,0,4]]  similar=[[0] * 5 in range(5)] print(similar) x in range(0,5):     y in range(0,5):         similar[x][y] = cosine_similarity(ur[x],ur[y])  similar

output:

[[array([[ 1.]]),   array([[ 0.6]]),   array([[ 0.37097041]]),   array([[ 0.80295507]]),   array([[ 0.]])],

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