FP-Growth Algorithm for Application in Research of the Basket Analysis

During the process of mining frequent item sets, when minimum support is little, the production of candidate sets is a kind of time-consuming and frequent operation in the mining algorithm. The FP growth algorithm does not need to produce the candidate sets, the database which provides the frequent item set is compressed to a frequent pattern tree (or FP tree), the frequent item set is mining by using of FP tree. For the sake of researching the Basket Analysis, the Frequent-Pattern is introduced, Visual C++ is applied to design the program to mine the frequent item sets. In view of the frequent K-item set, the various results are contrasted, the goods which is sell possibly at the same time in the supermarket is arranged in the same place.