Adaptive floating search methods in feature selection
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
IEEE Transactions on Neural Networks
Fast feature selection aimed at high-dimensional data via hybrid-sequential-ranked searches
Expert Systems with Applications: An International Journal
A system for classification of time-series data from industrial non-destructive device
Engineering Applications of Artificial Intelligence
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This work presents a Feature Selection Algorithm for optimization of a Probabilistic Neural Network. The aim of this Probabilistic Neural Network is classifying signals obtained from magnetic material samples where two micro-structural parameters were changed simultaneously. The combination of the Feature Selection Algorithm with the Probabilistic Neural Network shows both, classification rate outcomes and classification speed, higher than those coming from traditional Probabilistic Neural Networks.