This function resembles the MSE criterion, but measures the relative error with respect to the target value. Minimizing this function is equivalent to minimize
Please note that zero target values do undefine the function. This criterion isn't appropiate for small target values.
In a batch training mode, where all patterns are used to determine the gradient
, then the training optimizes the MAPE criterion.
Functions | |
| double | gnn_msre_e (gnn_criterion *crit, const gsl_vector *y, const gsl_vector *t) |
| The evaluation function. | |
| int | gnn_msre_dy (gnn_criterion *crit, const gsl_vector *y, const gsl_vector *t, gsl_vector *dy) |
| The gradient evaluation function. | |
| gnn_criterion * | gnn_msre_new (size_t size) |
| Creates a new gnn_msre criterion. | |
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This function implements the gnn_msre criterion's gradient evaluation function given by
Definition at line 139 of file gnn_msre.c. |
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This function corresponds to the evaluation of the MSRE criterion.
Definition at line 91 of file gnn_msre.c. |
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This function creates a new gnn_msre of the given size.
Definition at line 190 of file gnn_msre.c. |
1.2.18