Function Index

T |
| test, neural_net
| test_data, neural_net
| train, neural_net
| train_epoch, neural_net
| train_on_data, neural_net
| train_on_file, neural_net
| training_data, training_data
~ | training_data, training_data

> fann_type * test( | fann_type | * | input,
> | fann_type | * | desired_output | )

Test with a set of inputs, and a set of desired outputs.

> float test_data( | const | training_data | & | data | )

Test a set of training data and calculates the MSE for the training data.

> void train( | fann_type | * | input,
> | fann_type | * | desired_output | )

Train one iteration with a set of inputs, and a set of desired outputs.

> float train_epoch( | const | training_data | & | data | )

Train one epoch with a set of training data.

> void train_on_data( | const | training_data | & | data,
> | unsigned | int |  | max_epochs,
> | unsigned | int |  | epochs_between_reports,
> |  | float |  | desired_error | )

Trains on an entire dataset, for a period of time.

> void train_on_file( | const std:: | string | & | filename,
> | unsigned | int |  | max_epochs,
> | unsigned | int |  | epochs_between_reports,
> |  | float |  | desired_error | )

Does the same as train_on_data, but reads the training data directly from a file.

> training_data( |  | ) : train_data(NULL)

Default constructor creates an empty neural net.

> #ifdef USE_VIRTUAL_DESTRUCTOR virtual #endif ~training_data()

Provides automatic cleanup of data.
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