Practical Characteristics of Neural Network and Conventional Pattern Classifiers on Artificial and Speech Problems
@inproceedings{Lee1989PracticalCO,
title={Practical Characteristics of Neural Network and Conventional Pattern Classifiers on Artificial and Speech Problems},
author={Yuchun Lee and Richard Lippmann},
booktitle={NIPS},
year={1989}
}Eight neural net and conventional pattern classifiers (Bayesian-unimodal Gaussian, k-nearest neighbor, standard back-propagation, adaptive-stepsize back-propagation, hypersphere, feature-map, learning vector quantizer, and binary decision tree) were implemented on a serial computer and compared using two speech recognition and two artificial tasks. Error rates were statistically equivalent on almost all tasks, but classifiers differed by orders of magnitude in memory requirements, training time…
65 Citations
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