Enhancing IPADE algorithm with a different individual codification

Authors:
Isaac Triguero;Salvador García;Francisco Herrera
Affiliations:
Dept. of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;Dept. of Computer Science. University of Jaén, Jaén, Spain;Dept. of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
Venue:
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Year:
2011

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Abstract

Nearest neighbor is one of the most used techniques for performing classification tasks. However, its simplest version has several drawbacks, such as low efficiency, storage requirements and sensitivity to noise. Prototype generation is an appropriate process to alleviate these drawbacks that allows the fitting of a data set for nearest neighbor classification. In this work, we present an extension of our previous proposal called IPADE, a methodology to learn iteratively the positioning of prototypes using a differential evolution algorithm. In this extension, which we have called IPADECS, a complete solution is codified in each individual. The results are contrasted with non-parametrical statistical tests and show that our proposal outperforms previously proposed methods.