An Efficient Ant Colony Instance Selection Algorithm for KNN Classification

Author:

Miloud-Aouidate Amal1,Baba-Ali Ahmed Riadh1

Affiliation:

1. University of Science and Technology, Houari Boumediene, Bab Ezzouar Algiers, Algeria

Abstract

The extraordinary progress in the computer sciences field has made Nearest Neighbor techniques, once considered impractical from a standpoint of computation (Dasarathy et al., 2003), became feasible for real-world applications. In order to build an efficient nearest neighbor classifier two principal objectives have to be reached: 1) achieve a high accuracy rate; and 2) minimize the set of instances to make the classifier scalable even with large datasets. These objectives are not independent. This work addresses the issue of minimizing the computational resource requirements of the KNN technique, while preserving high classification accuracy. This paper investigates a new Instance Selection method based on Ant Colonies Optimization principles, called Ant Instance Selection (Ant-IS) algorithm. The authors have proposed in a previous work (Miloud-Aouidate & Baba-Ali, 2012a) to use Ant Colony Optimization for preprocessing data for Instance Selection. However to the best of the authors’ knowledge, Ant Metaheuristic has not been used in the past for directly addressing Instance Selection problem. The results of the conducted experiments on several well known data sets are presented and compared to those obtained using a number of well known algorithms, and most known classification techniques. The results provide evidence that: (1) Ant-IS is competitive with the well-known kNN algorithms; (2) The condensed sets computed by Ant-IS offers also better classification accuracy then those obtained by the compared algorithms.

Publisher

IGI Global

Subject

Decision Sciences (miscellaneous),Computational Mathematics,Computational Theory and Mathematics,Control and Optimization,Computer Science Applications,Modeling and Simulation,Statistics and Probability

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Selection of Representative Instances using Ant Colony: A Case Study in a Database of Children and Adolescents with Attention-Deficit/Hyperactivity Disorder;Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies;2022

2. An Improved Substation Equipment Recognition Algorithm by KNN Classification of Subspace Feature Vector;2021 China Automation Congress (CAC);2021-10-22

3. Substation Equipment 3D Identification Based on KNN Classification of Subspace Feature Vector;Journal of Intelligent Systems;2017-10-25

4. An Improved Ant-IS Algorithm for Intrusion Detection;International Journal of Applied Metaheuristic Computing;2014-01

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