Evolving optimal feature extraction using multi-objective genetic programming: a methodology and preliminary study on edge detection

Abstract

In this paper we describe a generic methodology to create an "optimal" feature extraction pre-processing stage for pattern classification. Our aim is to map the input data into a new, one-dimensional feature space in which separability is maximized under a simple thresholding classification. We have used multi-objective genetic programming with Pareto… (More)
DOI: 10.1145/1068009.1068143

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@inproceedings{Zhang2005EvolvingOF, title={Evolving optimal feature extraction using multi-objective genetic programming: a methodology and preliminary study on edge detection}, author={Yang Zhang and Peter Rockett}, booktitle={GECCO}, year={2005} }