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Performance Evaluation of Neural Network Decision Models
Bharat A. Jain and Barin N. Nag
Journal of Management Information Systems
Vol. 14, No. 2 (Fall, 1997), pp. 201-216
Published by: Taylor & Francis, Ltd.
Stable URL: http://www.jstor.org/stable/40398272
Page Count: 16
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Recently, promising results with neural networks have been reported for two-group classification problems such as bankruptcy prediction and thrift failures. Such applications are usually characterized by unequal frequencies of the two states of interest. This creates a major obstacle to effective performance evaluation of various decision models. Critical issues affecting the comparison include training sample design and the use of an appropriate performance metric. This paper addresses these two issues by comparing the performance of neural networks with that of statistical models for the decision problem of identifying successful new ventures.
Journal of Management Information Systems © 1997 Taylor & Francis, Ltd.