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

被引:3
|
作者
Zakaria, Wael [1 ]
Kotb, Yasser [1 ,2 ]
Ghaleb, Fayed F. M. [1 ]
机构
[1] Ain Shams Univ, Fac Sci, Dept Math, Div Comp Sci, Cairo, Egypt
[2] Al Imam Mohammad Ibn Saud Islamic Univ, Coll Comp & Informat Sci, Dept Informat Syst, Riyadh, Saudi Arabia
关键词
data mining; DNA microarray; mining association rules; parallel mining association rules; closed item sets; row enumeration; column enumeration; maximal high confident rules; bitwise operations; shared memory systems; task parallelism; DISCOVERY;
D O I
10.1504/IJDMB.2015.072091
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
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.
引用
收藏
页码:225 / 247
页数:23
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