The Robotics Institute
Search the site
RI | Publications | Classification Using Multi-Layered Perceptrons

Text only version of this site

Classification Using Multi-Layered Perceptrons
S. Piramuthu, M.J. Shaw, and J.A. Gentry
tech. report CMU-RI-TR-90-29, Robotics Institute, Carnegie Mellon University, December, 1990.

Jump to: Download | Abstract | Notes | Text Reference | BibTeX Reference

Download [Help]

Adobe portable document format (pdf) [1378 KB]

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

There has been an increasing interest in the applicability of neural networks in disparate domains. In this paper, we describe the use of multi-layered perceptrons, a type of neural network topology, for financial classification problems, within promising results. Back-propagation, which is the learning algorithm most often used in multi-layered perceptrons, however, is inherently an inefficient search procedure. We present improved procedures which have much better convergence properties. Using several financial classification applications as examples, we show the efficacy of using multi-layered perceptrons with improved learning algorithms. The modified learning algorithms have better performance, in terms of classification/prediction accuracies, than the methods previously used in the literature, such as probit analysis and similarity-based learning techniques.

Notes

Grant ID: DACA 76-89-C-0014

Number of pages: 36

Text Reference

S. Piramuthu, M.J. Shaw, and J.A. Gentry, Classification Using Multi-Layered Perceptrons, tech. report CMU-RI-TR-90-29, Robotics Institute, Carnegie Mellon University, December, 1990.

BibTeX Reference

@techreport{Piramuthu_1990_241,
   author = "Selwyn Piramuthu and Michael J Shaw and James A. Gentry",
   title = "Classification Using Multi-Layered Perceptrons",
   institution = "Robotics Institute, Carnegie Mellon University",
   month = "December",
   year = "1990",
   number = "CMU-RI-TR-90-29",
   address = "Pittsburgh, PA"
}


The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.
For updates and comments, please see these instructions.
This page maintained by robotwebmaster@ri.cmu.edu