A universal theorem on learning curves
Neural Networks
Statistical and neural classifiers: an integrated approach to design
Statistical and neural classifiers: an integrated approach to design
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
Experts' Boasting in Trainable Fusion Rules
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Quantization Complexity and Independent Measurements
IEEE Transactions on Computers
k-nearest neighbors directed noise injection in multilayer perceptron training
IEEE Transactions on Neural Networks
Multicategory nets of single-layer perceptrons: complexity and sample-size issues
IEEE Transactions on Neural Networks
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Equation for generalization error of Multinomial classifier is derived and tested. Particular attention is paid to imbalanced training sets. It is shown that artificial growth of training vectors of less probable class could be harmful. Use of predictive Bayes approach to estimate cell probabilities of the classifier reduces both the generalization error and effect of unequal training sample sizes.