Mining frequent closed patterns in microarray data

Abstract

Microarray data typically contains a large number of columns and a small number of rows, which poses a great challenge for existing frequent (closed) pattern mining algorithms that discover patterns in item enumeration space. In this paper, we propose two new algorithms that explore the row enumeration space to mine frequent closed patterns. Several experiments on real-life gene expression data show that the new algorithms are faster than existing algorithms, including CLOSET, CHARM, CLOSET+ and CARPENTER. © 2004 IEEE.