Anybody knows how to solve this problem? I'm studying collective intelligence now, and I compared with another example when I made this code. But It's getting error like this:
Traceback (most recent call last): File "<pyshell#8>", line 1, in
<module>
clust=clusters.hcluster(data) File "D:\Kuliah\smt1\Phyton Class\contoh coding\coding-collective
intelligence\myself_Maulida\bab3-documentClustering\clusters.py", line
78, in hcluster
for i in range(len(clust[0].vec))] TypeError: 'float' object has no attribute '__getitem__'
Here is my code, anybody can help? Thank you.
def hcluster(rows,distance=pearson):
distances={}
currentclustid=-1
#clusters are initially just the rows
clust=[bicluster(rows[i],id=i) for i in range(len(rows))]
while len(clust)>1:
lowestpair=(0.1)
closest=distance(clust[0].vec,clust[1].vec)
#loop through every pair looking for the smallest distance
for i in range(len(clust)):
for j in range(i+1,len(clust)):
#distance is the cache of distance calculations
if(clust[i].id,clust[j].id) not in distances:
distances[(clust[i].id,clust[j].id)]=distance(clust[i].vec,clust[j].vec)
d=distances[(clust[i].id,clust[j].id)]
if d<closest:
closest=d
lowestpair=(i,j)
#calculate the average of the two cluster
mergevec=[
(clust[lowestpair[0]].vec[i]+clust[lowestpair[1]].vec[i])/2.0
for i in range(len(clust[0].vec))]
#create the new cluster
newcluster=bicluster(mergevec,left=clust[lowestpair[0]],
right=clust[lowestpair[1]],
distance=closest,id=currentclustid)
#cluster ids that weren't in the original set are negative
currentclustid-=1
del clust[lowestpair[1]]
del clust[lowestpair[0]]
clust.append(newcluster)
return clust[0]