-mimic does well with structure
-representing PΘ Vo
-local optima
-probability theory
-time complexity
Clustering & EM
unsupervised learning
– supervised learning use labeled training data to generalize labels to new instances
– unsupervised learning make sense out of unlabeled data
Basic clustering problem
given: set of objects X
inter-object distances D(x,y) = D(y,x) x, yeX
output: partition pd(x) = pd(y)
if x &y in same cluster
