Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/70745
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Conference paper |
Title: | An experimental study of multi-objective evolutionary algorithms for balancing interpretability and accuracy in fuzzy rulebase classifiers for financial prediction |
Author: | Ghandar, A. Michalewicz, Z. |
Citation: | Proceedings of the 2011 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), 11-15 April, 2011, Paris: pp.1-6 |
Publisher: | IEEE |
Publisher Place: | USA |
Issue Date: | 2011 |
ISBN: | 9781424499335 |
Conference Name: | IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr) (2011 : Paris) |
Statement of Responsibility: | Adam Ghandar and Zbigniew Michalewicz |
Abstract: | This paper examines the advantages of simple models over more complex ones for financial prediction. This premise is examined using a genetic fuzzy framework. The interpretability of fuzzy systems is oftentimes put forward as a unique advantageous feature, sometimes to justify effort associated with using fuzzy classifiers instead of alternatives that can be more readily implemented using existing tools. Here we investigate if model interpretability can provide further benefits by realizing useful properties in computationally intelligent systems for financial modeling. We test an approach for learning momentum based strategies that predict price movements of the Bombay Stock Exchange (BSE). The paper contributes an experimental evaluation of the relationship between the predictive capability and interpretability of fuzzy rule based systems obtained using Multi- Objective Evolutionary Algorithms (MOEA.) |
Rights: | © Copyright 2011 IEEE |
DOI: | 10.1109/CIFER.2011.5953570 |
Published version: | http://dx.doi.org/10.1109/cifer.2011.5953570 |
Appears in Collections: | Aurora harvest Computer Science publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.