Performance Evaluation of Neural Network Decision Models.

Author List: Jain, Bharat A.; Nag, Barin N.;

Journal of Management Information Systems, 1997, Volume 14, Issue 2, Page 201-216.

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.

Keywords: logit models;neural networks;new ventures;sample design

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List of Topics

#215	0.449	data classification statistical regression mining models neural methods using analysis techniques performance predictive networks accuracy method variables prediction problem measure
#157	0.178	evaluation effectiveness assessment evaluating paper objectives terms process assessing criteria evaluations methodology provides impact literature potential important evaluated identifying multiple
#81	0.118	applications application reasoning approach cases support hypertext case-based prototype problems consistency developed benchmarking described efficient practical address activity demonstrate effective
#8	0.056	decision making decisions decision-making makers use quality improve performance managers process better results time managerial task significantly help indicate maker