Neural Network Model for Classification Algorithms and Its Application

Author

Ye Qian

Author_Institution

Sch. of Finance, Zhejiang Univ. of Finance & Econ., Hangzhou, China

fYear

2006

fDate

7-11 Aug. 2006

Firstpage

1177

Lastpage

1182

Abstract

Neural network-based systems that allow the system, through an analysis of historical data, to determine the relationship between account characteristics and the probability of default. The backpropagation algorithm - the multilayer feedforward network structure is described based on data with nine financial ratios from 81 firms listed in China. A simulation on network is made. Neural network model for classification algorithms are established. By varying network parameters we demonstrate that LevenbergMarque training error is smallest among 4 learning algorithms and its performance is better. Increasing the number of hidden layer can result in minor improvement.

Keywords

backpropagation; feedforward neural nets; finance; pattern classification; probability; LevenbergMarque training error; backpropagation algorithm; classification algorithm; financial ratio; learning algorithm; multilayer feedforward network; neural network model; Artificial neural networks; Backpropagation algorithms; Classification algorithms; Classification tree analysis; Feedforward neural networks; Finance; Mathematical model; Multi-layer neural network; Neural networks; Predictive models; Classification Algorithms; Financial Ratio; Neural Network; The Multilayer Feedforward Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2006. CCC 2006. Chinese

Conference_Location

Harbin

Print_ISBN

7-81077-802-1

Type

conf

DOI

10.1109/CHICC.2006.280600

Filename

4060266