Performance evaluation of neural network decision models

摘要: 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 interest. This creates a major obstacle to effective performance evaluation various decision models. Critical issues affecting comparison include training sample design use an appropriate metric. paper addresses these comparing that statistical models problem identifying successful new ventures.