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Constructing non-orthogonal feature bases

Proceedings of International Conference on Neural Networks (ICNN'96), 2002
A feature extraction algorithm based on self-organising maps is presented. The converged feature map can be interpreted as a non-orthogonal basis spanning the space of the input vectors. The new algorithm can be shown to be a generalization of the generalised Hebbian algorithm (GHA).
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Evolutionary Computation for Feature Selection and Feature Construction

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2016
Bing Xue 0001, Mengjie Zhang 0001
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Kaizen Programming for Feature Construction for Classification

2016
A data set for classification is commonly composed of a set of features defining the data space representation and one attribute corresponding to the instances’ class. A classification tool has to discover how to separate classes based on features, but the discovery of useful knowledge may be hampered by inadequate or insufficient features.
Vinícius Veloso de Melo, Wolfgang Banzhaf +1 more
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Construction robotics: review of intelligent features