@inproceedings{b2c0829a10fa402f8cd2d9dba53d2925,
title = "Determining Divisia rules using the aggregate feedforward neural network",
abstract = "This paper introduces a mechanism for generating human-readable and machine-executable rules that characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation. Divisia component data is used to train an Aggregate Feedforward Neural Network (AFFNN), a general-purpose connectionist architecture originally developed to assist with data mining activities. The rules extracted from the trained AFFNN meaningfully and, accurately describe inflation in terms of the Divisia component dataset.",
keywords = "Data mining, Divisia, Inflation, Neural network, Rule generation",
author = "Schmidt, {Vincent A.} and Binner, {Jane M.}",
year = "2003",
language = "English",
isbn = "1932415122",
series = "Proceedings of the International Conference on Artificial Intelligence IC-AI 2003",
pages = "68--74",
editor = "H.R. Arabnia and R. Joshua and Y. Mun and H.R. Arabnia and R. Joshua and Y. Mun",
booktitle = "Proceedings of the International Conference on Artificial Intelligence IC-AI 2003",
note = "Proceedings of the International Conference on Artificial Intelligence, IC-AI 2003 ; Conference date: 23-06-2003 Through 26-06-2003",
}