Performance Analysis on Advances in Frequent Pattern Growth Algorithm

In data mining, association-rules mining are a crucial technology. The Frequent-Growth (FP) algorithm is a well-known algorithm for association mining. However, FP-Growth method in mining requires two scans of the database which affects the process's efficiency. We have compared two different FP-Growth algorithms namely Painting-Growth algorithm as well as not Painting-Growth algorithm via the study of association mining and FP-Growth algorithm. With the FP-Growth algorithm, we have compared two different types of enhanced algorithms. Performance of these enhanced algorithms is absolutely better than FP-Growth algorithm, according to the experimental results. Painting-Growth algorithm has a data volume of greater than 1050 and also, N Painting-Growth algorithm has a data volume of less than 10000.