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supervised discrimination of clustered data via optimization of binary information gain. Induction over the unexplained: Integrated learning of concepts with both explainable and conventional aspects.mann machines: Constraint satisfaction networks that learn.gation learning for multi-layer feed-forward neural networks using the conjugate gradient method. ARTMAP: Supervised real-time learning and classiication of nonstationary data by a self-organizing neural network. Andrea Pohoreckyj Danyluk. Finding new rules for incomplete theories: explicit biases for induction with contextual information. International application of a new probability algorithm for the diagnosis of coronary artery disease. Transfer in neural networks 35 critical to learning systems of the future, which will require the ability to quickly adapt to new situations based on past experience. for past input into this research program. Tom Fawcett helped with many of the symbolic references. Alex Waibel suggested the application of transfer to speaker-dependent tasks. The heart disease data was collected by: beach and Cleveland Clinic Foundation. We used software distributed with McClelland and Rumelhart, 1988 ] for many of our simulations. A neural-net training program based on conjugate-gradient optimization. 0 0 0 0 1 1 0 1 1 1 1 0 0 0 0 1 1 0 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1 0 0 1 Source 1 Feature 1 HU 1 HU1 HU 2 0 0 0 0 1 1 0 1 1 1 1 0 0 0 0 1 1 0 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1 0 0 1 HU 1 HU1 HU 2 HU 3 0 0 0 0 1 1 0 1 1 1 1 0 0 0 0 1 1 0 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1 0 0 1 Source 3