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    Neural Network Data Analysis Using Simulnet™

Neural Network Data Analysis Using Simulnet™

Edward J. Rzempoluck
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      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.
      Format: CONTRIBUTORS: Edward J. Rzempoluck EAN: 9780387982557 COUNTRY: United States PAGES: WEIGHT: 602 g HEIGHT: 244 cm
      PUBLISHED BY: Springer-Verlag New York Inc. DATE PUBLISHED: 1997-12-12 CITY: GENRE: COMPUTERS / Artificial Intelligence / General, COMPUTERS / Database Administration & Management, MATHEMATICS / Probability & Statistics / General WIDTH: 170 cm SPINE:

      Book Themes:

      Probability and statistics, Databases, Artificial intelligence

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      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.
      Format: CONTRIBUTORS: Edward J. Rzempoluck EAN: 9780387982557 COUNTRY: United States PAGES: WEIGHT: 602 g HEIGHT: 244 cm
      PUBLISHED BY: Springer-Verlag New York Inc. DATE PUBLISHED: 1997-12-12 CITY: GENRE: COMPUTERS / Artificial Intelligence / General, COMPUTERS / Database Administration & Management, MATHEMATICS / Probability & Statistics / General WIDTH: 170 cm SPINE:

      Book Themes:

      Probability and statistics, Databases, Artificial intelligence

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