Problem 6.6 Find frequent itemsets, using both apriori and FP-tree
For apriori: show each C_k an L_k, as demonstrated in class
For FP: show each tree iteration
T100	{S,T,A,N,D}				min_sup = 60%
T200	{M,A,N,E,S}				60% of 5 transactions = 3
T300	{M, E,N,D,S}
T400	{S,A,D,L,Y}
T500	{S,A,N,D,M}
Create the strong association rules that can be inferred from L_2.
Create the strong assocation rules for set SAN.
To create association rules where min_sup = 60% and min_conf = 80%:
For each set, L, generate all non-empty sets. For each non-empty subset, s:
	support_count is simply how often it appears in the list.
	support is support_count over total # of transactions.
	confidence = support_count(L) / support_count (s)
	BTW, this is P(Y and K)/ P(K). It's conditional probability...
	More precisely, it's also P(Y U K)/P(K)