Geometry neural network

Studies of these kinds are of particular importance to all theoretical information storage and retrieval systems incorporating some form of geometry modification, such as those modeled by certain neural networks. 

Overfitting is a potentially serious problem in neural networks. It is tackled in two ways (1) by continually monitoring the quality of training as it occurs using a test set, and (2) by ensuring that the geometry of the network (its size and the way the nodes are connected) is appropriate for the size of the dataset. 

Molecular geometries were optimized by the AMI method Chemometrics and neural network methods... 

In the 1960 s, Edward Feigenbaum and other scientists at Stanford University built two early expert systems DENDRAL, which classified chemicals, and MYCIN, which identified diseases. These early expert systems were cumbersome to modify because they had hard-coded rules. By 1970, the OPS expert system shell, with variable rule sets, had been released by Digital Equipment Corporation as the first commercial expert system shell. In addition to expert systems, neural networks became an important area of artificial intelligence in the 1970 s and 1980 s. Frank Rosenblatt introduced the Perceptron in 1957, but it was Perceptrons An Introduction to Computational Geometry (1969), by Minsky and Seymour Papert, and the two-volume Parallel Distributed Processing Explorations in the Microstructure of Cognition (1986),... 

Bishop, C.M. (1996) Neural Networks for Pattern Recognition, Oxford University Press, Oxford, 504 pp. Blackith, R.E. and Reyment, R.A. (1991) Multivariate Morphometries, Academic Press, London, 412 pp. Bookstein, F.L. (1991) Morphometric Tools for Landmark Data Geometry and Biology, Cambridge University Press, Cambridge, 435 pp. 

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