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EPACO: a novel ant colony optimization for emerging patterns based classification

delete2017-05-18
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Z
Zulfiqar Ali *
W
Waseem Shahzad
DOI:10.1007/s10586-017-0894-4delete
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摘要

摘要

En 中文
In this paper, a novel approach for discovering emerging patterns has been proposed. Majority of the existing algorithms for the discovery of emerging patterns are tree-based which involve growth and shrinking of trees for this purpose. These algorithms follow greedy search approach for discovery of emerging patterns. The proposed approach utilizes the diversity of ant colony optimization and avoids complexity and greedy search of tree-based algorithms for discovery of emerging patterns. The experiments show that the proposed approach provides higher accuracy than existing state of the art classifiers as well as emerging pattern-based classifiers.
Keyword:
Emerging patterns
Patterns discovery
Data mining
Classification
Ant colony optimization
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期刊

C
Cluster Computing-The Journal of Networks Software Tools and Applications
IF:
4.1
论文数:
5.1K
被引数:
7.5K

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