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DOI: 10.14569/IJACSA.2017.080108
PDF

Comparative Analysis and Survey of Ant Colony Optimization based Rule Miners

Author 1: Zulfiqar Ali
Author 2: Waseem Shahzad

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 1, 2017.

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Abstract: In this research study, we analyze the performance of bio inspired classification approaches by selecting Ant-Miners (Ant-Miner, cAnt_Miner, cAnt_Miner2 and cAnt_MinerPB) for the discovery of classification rules in terms of accuracy, terms per rule, number of rules, running time and model size discovered by the corresponding rule mining algorithm. Classification rule discovery is still a challenging and emerging research problem in the field of data mining and knowledge discovery. Rule based classification has become cutting edge research area due to its importance and popular application areas in the banking, market basket analysis, credit card fraud detection, costumer behaviour, stock market prediction and protein sequence analysis. There are various approaches proposed for the discovery of classification rules like Artificial Neural Networks, Genetic Algorithm, Evolutionary Programming, SVM and Swarm Intelligence. This research study is focused on classification rule discovery by Ant Colony Optimization. For the performance analysis, Myra Tool is used for experiments on the 18 public datasets (available on the UCI repository). Data sets are selected with varying number of instances, number of attributes and number of classes. This research paper also provides focused survey of Ant-Miners for the discovery of classification rules.

Keywords: Classification Rule; Ant Colony Optimization; Data Mining; Rule Discovery

Zulfiqar Ali and Waseem Shahzad, “Comparative Analysis and Survey of Ant Colony Optimization based Rule Miners” International Journal of Advanced Computer Science and Applications(IJACSA), 8(1), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080108

@article{Ali2017,
title = {Comparative Analysis and Survey of Ant Colony Optimization based Rule Miners},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080108},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080108},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {1},
author = {Zulfiqar Ali and Waseem Shahzad}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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