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Hypercube Neural Network Algorithm for Classification

Abstract : The Hypercube Neural Network Algorithm is a novel supervised method for classification. One hypercube is defined per class in the attribute space based on the training data. Each dimension of a hypercube is set to cover the full range of values in the class. The hypercube learning is therefore a rapid, one-shot form of learning. This paper presents three versions of the algorithm: hypercube without neurons; with simple neurons; and with adaptive activation function neurons. The methods are tested and evaluated on several diverse publically available data sets and compared with published results obtained on these data when using alternative methods.
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https://hal.inria.fr/hal-01571377
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Submitted on : Wednesday, August 2, 2017 - 11:42:03 AM
Last modification on : Wednesday, December 30, 2020 - 9:22:02 AM

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Dominic Palmer-Brown, Chrisina Jayne. Hypercube Neural Network Algorithm for Classification. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. pp.41-51, ⟨10.1007/978-3-642-23957-1_5⟩. ⟨hal-01571377⟩

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