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Type: Journal article
Title: Fast algorithms for mining Strong Jumping Emerging Patterns using the contrast pattern tree
Author: Liu, Q.
Shi, P.
Hu, Z.
Citation: ICIC Express Letters, Part B: Applications, 2013; 4(1):121-128
Publisher: ICIC International
Issue Date: 2013
ISSN: 2185-2766
Statement of
Quanzhong Liu, Peng Shi and Zhengguo Hu
Abstract: Efficient 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.
Keywords: CP-tree
Data mining
Pattern pruning
Rights: Copyright status unknown
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Electrical and Electronic Engineering publications

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