Association_Rule_Mining_using_Trie

###Implementation of Association Rule Mining in Java, using Trie data structure

Association rule mining is a two-step process:

1. Frequent itemset generation and
2. Rule generation.

Apriori algorithm is used to generate frequent itemset followed by rule generation.
Support and confidence, the two statistical measures are used to refine itemset and rules, respectively.

References:

1. Agrawal, R., & Srikant, R. (1994, September). Fast algorithms for mining association rules. In Proc. 20th int. conf. very large data bases, VLDB (Vol. 1215, pp. 487-499).
2. Bodon, F., & R'f3nyai, L. (2003). Trie: An alternative data structure for data mining algorithms. Mathematical and Computer Modelling, 38(7), 739-751.
3. http://stackoverflow.com/questions/127704/algorithm-to-return-all-combinations-of-k-elements-from-n
4. http://weka.sourceforge.net/doc.stable/weka/associations/Apriori.html