Analyzing MSI rules for the USA extracted from a feedforward neural network

Vincent A. Schmidt*, Jane M. Binner

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

This paper introduces a mechanism for generating a series of rules that characterize the money-price relationship for the USA, defined as the relationship between the rate of growth of the money supply and inflation. Monetary Services Indicator (MSI) component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of the MSI component dataset.

Original languageEnglish
Title of host publicationProceedings of the 2007 International Conference on Artificial Intelligence, ICAI 2007
Pages265-271
Number of pages7
Volume1
Publication statusPublished - 1 Dec 2007
Event2007 International Conference on Artificial Intelligence, ICAI 2007 - Las Vegas, NV, United Kingdom
Duration: 25 Jun 200728 Jun 2007

Conference

Conference2007 International Conference on Artificial Intelligence, ICAI 2007
CountryUnited Kingdom
CityLas Vegas, NV
Period25/06/0728/06/07

Keywords

  • Data mining
  • Inflation
  • MSI
  • Neural network
  • Rule generation

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  • Cite this

    Schmidt, V. A., & Binner, J. M. (2007). Analyzing MSI rules for the USA extracted from a feedforward neural network. In Proceedings of the 2007 International Conference on Artificial Intelligence, ICAI 2007 (Vol. 1, pp. 265-271)