Apriori Algorithm
Apriori Algorithm Apriori algorithm is given by R. Agrawal and R. Srikant in 1994 for finding frequent itemsets in a dataset for boolean association rule. Name of the algorithm is Apriori because it uses prior knowledge of frequent itemset properties. We apply an iterative approach or level-wise search where k-frequent itemsets are used to find k+1 itemsets. To improve the efficiency of level-wise generation of frequent itemsets, an important property is used called Apriori property which helps by reducing the search space. Apriori property: All non-empty subset of frequent itemset must be frequent. The key concept of Apriori algorithm is its anti-monotonicity of support measure. Apriori assumes that All subsets of a frequent itemset must be frequent(Apriori propertry). If an itemset is infrequent, all its supersets will be infrequent. Step-1: K=1 (I) Create a table containing support count of each item present in dataset – Called C1(candidate set) (...