Handbooks of Research Methods and Applications series
Edited by Charlie Karlsson, Martin Andersson and Therese Norman
Chapter 8: Neural networks: a class of flexible non-linear models for regression and classification
Neural networks form a field of research that has enjoyed rapid expansion and increasing popularity in recent years. The exuberance of this growth has been accompanied by exaggerated claims concerning the technological potential of neural networks. In addition, a definite mystique perceived by those outside the field arises from the origins of neural networks in the study of natural neural systems, and in the associated metaphorical jargon in the field. Both the exaggerated claims and the mystique may have acted to lessen the amount of serious attention given to neural networks in economic geography and regional science. This chapter is intended as a convenient resource for those interested in a more fundamental view of the neural network modelling approach. The primary aim is to discuss some issues that are crucial for the design and understanding of neural network models, with a strong emphasis on their practical use for solving regression and classification problems.
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