New approach for frequent item set generation based on mirabit hashing algorithm

In today's scenario of data mining, there are so many upgraded versions of traditional Apriori has been launched in association due to its limitation of suffering from number of inefficiencies. Which have procreate other algorithms. The actual concept of this research topic is also one of them and it mainly focus on the description of the new version of hash based association using association rule mining. There are so many problems in traditional Apriori like low efficiency, more consuming time etc. So considering one of this problem traditional Apriori is the basic algorithm in this research work and the presented new approach of this algorithm varies from Mirabit algorithm using Apriori property with new parameters. The main aim of this new Mirabit hashing algorithm is to improve the overall performance of algorithm compare to its referred methodology and evaluate the final bucket count of item set closely nearest to given minimum support using new hash functions.