| ### Index
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Russell D. Reed and Robert J. Marks II
Copyright © 1999 Massachusetts Institute of Technology

## Index

### D

Data, and generalization, 242-248
Davidon-Fletcher-Power (DFP) method, 174-175
Decay. See Weight decay
Decision tree classifier, 108-109, 152, 217
Defining length of schemata, 188
Degrees of freedom, 245-246
Delta attenuation, 72, 84-85
Delta-bar-delta algorithm, 137-139, 140-141, 152
justification for, 139-140
Delta rule, 29, 86. See also Widrow-Hoff learning rule
Delta values, 55-57
Dendrites, 1
Density, 243
Dependency, 50-51
Depth versus size, 38-41
Derivative calculation, 49, 53-57, 66
Deterministic methods, 158, 159-175
DFP (Davidon-Fletcher-Power) method, 174-175
Diagonal approximation, 131
Dichotomies, 20-22, 42-44
Differentiability, 156
Direction set method, 161-163
Discriminant analysis, 107-108, 306-310
Divide and conquer, 204
Dynamic node creation, 199-201

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