Direct Parallel Perceptrons (DPPs): Fast Analytical Calculation of the Parallel Perceptrons Weights With Margin Control for Classification Tasks

Parallel perceptrons (PPs) are very simple and efficient committee machines (a single layer of perceptrons with threshold activation functions and binary outputs, and a majority voting decision scheme), which nevertheless behave as universal approximators. The parallel delta (P-Delta) rule is an eff...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2011-11, Vol.22 (11), p.1837-1848
Hauptverfasser:	Fernandez-Delgado, M., Ribeiro, J., Cernadas, E., Ameneiro, S. B.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Activation Algorithmics. Computability. Computer arithmetics Algorithms Analytical closed-form weight calculation Applied sciences Artificial Intelligence Classification Classification - methods Closed-form solutions Computer science control theory systems Connectionism. Neural networks Data processing. List processing. Character string processing Databases, Factual Exact sciences and technology Kernel Linear approximation linear computational complexity Linear Models margin maximization Mathematical analysis Mathematical models Memory and file management (including protection and security) Memory organisation. Data processing Neural Networks (Computer) online learning parallel delta rule parallel perceptrons pattern classification Reproducibility of Results Software Statistical learning Studies Support vector machines Tasks Theoretical computing Thresholds Training
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