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What is Explanatory Capacity of Artificial Neural Networks

Encyclopedia of Information Science and Technology, Fourth Edition
It consists in the implementation of methods that are able to determine the relative contribution of each ANN input variable to the ANN output. See Gevrey et al. (2003) for further details.
Published in Chapter:
Applications of Artificial Neural Networks in Economics and Finance
Iva Mihaylova (University of St. Gallen, Switzerland)
Copyright: © 2018 |Pages: 11
DOI: 10.4018/978-1-5225-2255-3.ch575
Abstract
Artificial neural Networks (ANNs) are a powerful technique for multivariate dependence analysis. Originally inspired by neuroscience, ANNs are becoming an increasingly attractive analytic tool for applications in the area of economics and finance due to the flexible solutions they offer. The purpose of this article is to present such important applications with an emphasis on recent research trends. The contributions are grouped as follows: ANNs (1) for prediction, (2) for classification and (3) for modelling. The chapter concludes with the future trends in the ANNs research in economics and finance.
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