FINDING OF REPEATED ITEMSETS USING GENETIC ALGORITHM

Extracting high profit itemsets from a deed database allude to the finding of itemsets with high profits. In existing algorithms they acquire the difficulty of producing huge numbers of candidate itemsets reduces the extracting performance in conditions of time and memory requirement. This difficulty may become poorer when the database contains long transactions. Therefore utility pattern growth (UP - Growth) and UP - Growth+ method gives out compact frequent item sets that is comparatively a good result when compared to alrea dy existing method. Even though it gives out compact frequent itemsets, UP - Growth generates minimum utility itemsets and UP - Growth+ generates maximum utility itemsets. But there is a difficulty for the provider to find frequent itemsets based on profit fro m the entire dataset . By considering this problem, an innovative solution has been proposed for finding frequent itemsets from the entire database according to the customer purchase details. Our main aim is to view the frequent itemsets from the combinati on of minimum and maximum utility i temsets using GENETIC algorithm