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Neural Networks: An Introductory Guide for Social Scientists / Edition 1

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Overview

Neural networks have influenced many areas of research but have only just started to be utilized in social science research. Neural Networks provides the first accessible introduction to this analysis as a powerful method for social scientists. It provides numerous studies and examples that illustrate the advantages of neural network analysis over other quantitative and modeling methods in wide-spread use among social scientists. The author, G. David Garson, presents the methods in an accessible style for the reader who does not have a background in computer science. Features include an introduction to the vocabulary and framework of neural networks, a concise history of neural network methods, a substantial review of the literature, detailed neural network applications in the social sciences, coverage of the most common alternative neural network models, methodological considerations in applying neural networks, examples using the two leading software packages for neural network analysis, and numerous illustrations and diagrams.
This introductory guide to using neural networks in the social sciences will enable students, researchers, and professionals to utilize these important new methods in their research and analysis.
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Product Details

Meet the Author

G David Garson is Full Professor of Political Science at North Carolina State University
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Table of Contents

Introduction to Neural Network Analysis
The Terminology of Neural Network Analysis
The Backpropagation Model
Alternative Network Paradigms
Methodological Considerations
Neural Network Software
Example
Analysing Census Data with Neural Connection
Conclusion
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