Analyzing Working of FP-Growth Algorithm for Frequent Pattern Mining
International journal of research studies in computer science and engineering · 2017
Frequent Itemset -It refers to a set of items that frequently appear together, for example, milk and bread. Frequent Subsequence -A sequence of patterns that occur frequently such as purchasing a camera is followed by the memory card. Frequent Sub Structure -Substructure refers to different structural forms, which may be combined with itemsets or subsequences.FP-Growth algorithm is the most popular algorithm for pattern mining.It is based on divide and conquer strategy.Compress the database providing frequent sets and divide this compressed database into a set of conditional databases, each related to a frequent set and apply data mining on each database. DETAILED WORKING OF FP-GROWTH ALGORITHMThe FP-Growth algorithm allows the discovery of frequent itemset without generating candidate itemset.It is a two-step approach mentioned as under [4,5].1) Firstly a compact data structure is built which is referred as FP-tree.It is built using two passes over the data-set.2) Traverse through FP-Tree and extract frequently occurring itemsets.