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About Validating A Neural Network Application: The Case of Financial Diagnosis
The document discusses validating a neural network application for financial diagnosis. It proposes five bases for evaluating the suitability of a neural network model for a real problem: 1) the propositions made about the neural network in the application area, 2) theory of the application area, 3) validity of the data sets, 4) statistical validation of the propositions, and 5) analysis of the model's behavior and representations. It then applies these five bases to evaluate a multilayer perceptron model of financial diagnosis, comparing the model's performance, representations, and behavior to existing theories and models of financial diagnosis.
Detailed Information
| Author: | ['edinutza_pop'] |
|---|---|
| Publication Year: | 2012 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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