Generalization in Threshold Networks Combined Decision Trees and Combined Mask Perceptrons 1998 1 citations ? 1 self
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Author: by Llew Mason Peter Bartlett Mostefa Golea
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Abstract: We derive an upper bound on the generalization error of classifiers from a certain class of threshold networks. The bound depends on the margin of the classifier and the average complexity of the hidden units (where the average is over the weights assigned to each hidden unit). By representing convex combinations of decision trees or mask perceptrons as such threshold networks we obtain similar bounds on the generalization error of these classifiers.
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