Abstract

This work proposes an effective synergy of the Intervals׳ Number k-nearest neighbor (INknn) classifier, that is a granular extension of the conventional knn classifier in the metric lattice of Intervals׳ Numbers (INs), with the gravitational search algorithm (GSA) for stochastic search and optimization. Hence, the gsaINknn classifier emerges whose effectiveness is demonstrated here on 12 benchmark classification datasets. The experimental results show that the gsaINknn classifier compares favorably with alternative classifiers from the literature. The far-reaching potential of the gsaINknn classifier in computing with words is also delineated.

Citation

Y. Jamshidi, V.G. Kaburlasos, “gsaINknn: A GSA optimized, lattice computing knn classifier”, Engineering Applications of Artificial Intelligence, vol. 35, pp. 277-285, 2014.

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