Output of nn_cv application. |
Output format of the application for training and testing MLP using cross-validation techniques
The application print on standard output the following informations:
- General information about cross-validation: number of folds, number of classes.
- Structure: type of MLP, number of hidden layers, hidden units, inputs, outputs.
- Type of learning algorithm, its parameters and stop conditions.
- Training and testing result for each fold: Normalized RMS error, iterations, number of errors and error rate,
- Overall results of cross-validation: Number of errors and error rate, confusion matrix
- Elapsed CPU time
See also nn_cv
Example:
Alphabetic index Hierarchy of classes