Liu, Q.Shi, P.Hu, Z.2013-11-112013-11-112013ICIC Express Letters, Part B: Applications, 2013; 4(1):121-1282185-2766http://hdl.handle.net/2440/80824Efficient mining of Strong Jumping Emerging Patterns (SJEPs) is useful for constructing accurate classifiers. The method for mining SJEPs based on a contrast pattern tree structure (CP-Tree) has been demonstrated to perform extremely well for a low-dimensional dataset. In the method, a large number of non-minimal JEPs are generated during the mining process. So, it is unable to handle higher-dimensional attributes. In this paper, we propose a novel pattern pruning technique that dramatically reduces the search space. The CP-tree method is greatly improved by the proposed pattern pruning technique. Experiments are performed on two high-dimensional cancer datasets. Compared with the original CP-tree algorithm, the results show that the improved CP-tree algorithm is substantially faster, and able to handle higher-dimensional attributes.enCopyright status unknownCP-treeData miningPattern pruningSJEPsJournal article00201266452-s2.0-8487540210420535Shi, P. [0000-0001-8218-586X]