A connectionist approach to producing rules describing monthly UK Divisia data

Vincent A. Schmidt; Jane M. Binner

A connectionist approach to producing rules describing monthly UK Divisia data

Vincent A. Schmidt, Jane M. Binner

Finance

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper demonstrates a mechanism, whereby rules can be extracted from a feedforward neural network trained to characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation. Monthly Divisia component data is encoded and used to train a group of candidate connectionist architectures. One candidate is selected for rule extraction, using a custom decompositional extraction algorithm that generates rules in human-readable and machine-executable form. Rule and network accuracy are compared, and comments are made on the relationships expressed within the discovered rules. The types of discovered relationships could be used to guide monetary policy decisions.

Original language	English
Title of host publication	Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications
Pages	468-474
Number of pages	7
Publication status	Published - 2008
Event	2008 International Conference on Artificial Intelligence, ICAI 2008 and 2008 International Conference on Machine Learning; Models, Technologies and Applications, MLMTA 2008 - Las Vegas, NV, United States Duration: 14 Jul 2008 → 17 Jul 2008

Publication series

Name	Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications

Conference

Conference	2008 International Conference on Artificial Intelligence, ICAI 2008 and 2008 International Conference on Machine Learning; Models, Technologies and Applications, MLMTA 2008
Country/Territory	United States
City	Las Vegas, NV
Period	14/07/08 → 17/07/08

Keywords

Data mining
Divisia
Inflation
Neural Network
Rule generation

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics
Software
Computer Science Applications

Cite this

Schmidt, V. A., & Binner, J. M. (2008). A connectionist approach to producing rules describing monthly UK Divisia data. In Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications (pp. 468-474). (Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications).

Schmidt, Vincent A. ; Binner, Jane M. / A connectionist approach to producing rules describing monthly UK Divisia data. Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications. 2008. pp. 468-474 (Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications).

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title = "A connectionist approach to producing rules describing monthly UK Divisia data",

abstract = "This paper demonstrates a mechanism, whereby rules can be extracted from a feedforward neural network trained to characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation. Monthly Divisia component data is encoded and used to train a group of candidate connectionist architectures. One candidate is selected for rule extraction, using a custom decompositional extraction algorithm that generates rules in human-readable and machine-executable form. Rule and network accuracy are compared, and comments are made on the relationships expressed within the discovered rules. The types of discovered relationships could be used to guide monetary policy decisions.",

keywords = "Data mining, Divisia, Inflation, Neural Network, Rule generation",

author = "Schmidt, {Vincent A.} and Binner, {Jane M.}",

year = "2008",

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series = "Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications",

pages = "468--474",

booktitle = "Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications",

note = "2008 International Conference on Artificial Intelligence, ICAI 2008 and 2008 International Conference on Machine Learning; Models, Technologies and Applications, MLMTA 2008 ; Conference date: 14-07-2008 Through 17-07-2008",

}

Schmidt, VA & Binner, JM 2008, A connectionist approach to producing rules describing monthly UK Divisia data. in Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications. Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications, pp. 468-474, 2008 International Conference on Artificial Intelligence, ICAI 2008 and 2008 International Conference on Machine Learning; Models, Technologies and Applications, MLMTA 2008, Las Vegas, NV, United States, 14/07/08.

A connectionist approach to producing rules describing monthly UK Divisia data. / Schmidt, Vincent A.; Binner, Jane M.
Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications. 2008. p. 468-474 (Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This paper demonstrates a mechanism, whereby rules can be extracted from a feedforward neural network trained to characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation. Monthly Divisia component data is encoded and used to train a group of candidate connectionist architectures. One candidate is selected for rule extraction, using a custom decompositional extraction algorithm that generates rules in human-readable and machine-executable form. Rule and network accuracy are compared, and comments are made on the relationships expressed within the discovered rules. The types of discovered relationships could be used to guide monetary policy decisions.

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KW - Inflation

KW - Neural Network

KW - Rule generation

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BT - Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications

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Schmidt VA, Binner JM. A connectionist approach to producing rules describing monthly UK Divisia data. In Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications. 2008. p. 468-474. (Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications).

A connectionist approach to producing rules describing monthly UK Divisia data

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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