n documents clustering using a precomputed similarity metric between a pair
of documents.
Code so Far
Sim=np.zeros((n, n)) # create a numpy arrary
i=0
j=0
for i in range(0,n):
for j in range(i,n):
if i==j:
Sim[i][j]=1
else:
Sim[i][j]=simfunction(list_doc[i],list_doc[j]
Hello,
I have n documents and want to use precomputed similarity mertric between a
pair of documents for clustering.
I created a 2 dim numpy Array say X, containing similarity score for every
pair of documents.
Also
type(X) and X.shape gives the output as
(n, n)
Then I create a cluster object us
