A Fast Algorithm for Gibbs Sampling Association Rule Based on Hash
The Gibbs sampling algorithm,as a feature selection method,has shown good performance in association rule mining.In order to further accelerate the association rule mining algorithm based on Gibbs sampling,a Gibbs sampling association rule mining algorithm based on hash structure is proposed.This algorithm improves the storage method of binary data,establishes a decimal array,and inserts non duplicate data and its support into the hash table.The experimental results on real datasets show that the proposed algorithm has better advantages in terms of time cost compared to the original algorithm,and the increased spatial cost is within an acceptable range.
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