PMCR-Miner: parallel maximal confident association rules miner algorithm for microarray data set

摘要

The MCR-Miner algorithm is aimed to mine all maximal high confident association rules form the microarray up/down-expressed genes data set. This paper introduces two new algorithms: IMCR-Miner and PMCR-Miner. The IMCR-Miner algorithm is an extension of the MCR-Miner algorithm with some improvements. These improvements implement a novel way to store the samples of each gene into a list of unsigned integers in order to benefit using the bitwise operations. In addition, the IMCR-Miner algorithm overcomes the drawbacks faced by the MCR-Miner algorithm by setting some restrictions to ignore repeated comparisons. The PMCR-Miner algorithm is a parallel version of the new proposed IMCR-Miner algorithm. The PMCR-Miner algorithm is based on shared-memory systems and task parallelism, where no time is needed in the process of sharing and combining data between processors. The experimental results on real microarray data sets show that the PMCR-Miner algorithm is more efficient and scalable than the counterparts.