pair attribute, learning algorithm
We present the Pair Attribute Learning (PAL) algorithm for the selection of relevant inputs and network topology. Correlations on training instance pairs are used to drive network construction of a single-hidden layer MLP. Results on nine learning problems demonstrate 70% less complexity, on average, without a significant loss of accuracy.
Original Publication Citation
Henderson, E., and Martinez, T. R., "Pair Attribute Learning: Network Construction Using Pair Features", Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'2, pp. 2556-2561, 22.
BYU ScholarsArchive Citation
Martinez, Tony R. and Henderson, Eric K., "Pair Attribute Learning: Network Construction Using Pair Features" (2002). All Faculty Publications. 1074.
Physical and Mathematical Sciences
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