Neural Network Data Analysis Using Simulnet (TM) (Paperback, Softcover reprint of the original 1st ed. 1998)

This book and software package complements the traditional data analysis tools already widely available. It presents an introduction to the analysis of data using neural network functions such as multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalised regression neural networks, learning quantizer networks, and self-organising feature maps. In an easy-to-use, Windows-based environment it offers a wide range of data analytic tools which are not usually found together: genetic algorithms, probabilistic networks, as well as a number of related techniques that support these. Readers are assumed to have a basic understanding of computers and elementary mathematics, allowing them to quickly conduct sophisticated hands-on analyses of data sets.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Release date:	April 2013
First published:	1998
Authors:	Edward J. Rzempoluck
Dimensions:	280 x 210 x 13mm (L x W x T)
Format:	Paperback
Pages:	226
Edition:	Softcover reprint of the original 1st ed. 1998
ISBN-13:	978-1-4612-7262-5
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	1-4612-7262-9
Barcode:	9781461272625

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