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Cluster Computing

, Volume 21, Issue 1, pp 453–467 | Cite as

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

  • Zulfiqar AliEmail author
  • Waseem Shahzad
Article
  • 126 Downloads

Abstract

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.

Keywords

Emerging patterns Patterns discovery Data mining Classification Ant colony optimization 

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.National University of Computer and Emerging SciencesIslamabadPakistan

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