Function Index
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F
 fann_cascadetrain_on_data
 fann_cascadetrain_on_file
 fann_clear_scaling_params
 fann_copy
 fann_create_from_file
 fann_create_shortcut
 fann_create_shortcut_array
 fann_create_sparse
 fann_create_sparse_array
 fann_create_standard
 fann_create_standard_array
 fann_create_train
 fann_create_train_array
 fann_create_train_from_callback
 fann_create_train_pointer_array
 fann_descale_input
 fann_descale_output
 fann_descale_train
 fann_destroy
 fann_destroy_train
 fann_disable_seed_rand
 fann_duplicate_train_data
 fann_enable_seed_rand
 fann_get_activation_function
 fann_get_activation_steepness
 fann_get_bias_array
 fann_get_bit_fail
 fann_get_bit_fail_limit
 fann_get_cascade_activation_functions
 fann_get_cascade_activation_functions_count
 fann_get_cascade_activation_steepnesses
 fann_get_cascade_activation_steepnesses_count
 fann_get_cascade_candidate_change_fraction
 fann_get_cascade_candidate_limit
 fann_get_cascade_candidate_stagnation_epochs
 fann_get_cascade_max_cand_epochs
 fann_get_cascade_max_out_epochs
 fann_get_cascade_min_cand_epochs
 fann_get_cascade_min_out_epochs
 fann_get_cascade_num_candidate_groups
 fann_get_cascade_num_candidates
 fann_get_cascade_output_change_fraction
 fann_get_cascade_output_stagnation_epochs
 fann_get_cascade_weight_multiplier
 fann_get_connection_array
 fann_get_connection_rate
 fann_get_decimal_point
 fann_get_errno
 fann_get_errstr
 fann_get_layer_array
 fann_get_learning_momentum
 fann_get_learning_rate
 fann_get_max_train_input
 fann_get_max_train_output
 fann_get_min_train_input
 fann_get_min_train_output
 fann_get_MSE
 fann_get_multiplier
 fann_get_network_type
 fann_get_num_input
 fann_get_num_layers
 fann_get_num_output
 fann_get_quickprop_decay
 fann_get_quickprop_mu
 fann_get_rprop_decrease_factor
 fann_get_rprop_delta_max
 fann_get_rprop_delta_min
 fann_get_rprop_delta_zero
 fann_get_rprop_increase_factor
 fann_get_sarprop_step_error_shift
 fann_get_sarprop_step_error_threshold_factor
 fann_get_sarprop_temperature
 fann_get_sarprop_weight_decay_shift
 fann_get_total_connections
 fann_get_total_neurons
 fann_get_train_error_function
 fann_get_train_input
 fann_get_train_output
 fann_get_train_stop_function
 fann_get_training_algorithm
 fann_get_user_data
 fann_get_weights
 fann_init_weights
 fann_length_train_data
 fann_merge_train_data
 fann_num_input_train_data
 fann_num_output_train_data
 fann_print_connections
 fann_print_error
 fann_print_parameters
 fann_randomize_weights
 fann_read_train_from_file
 fann_reset_errno
 fann_reset_errstr
 fann_reset_MSE
 fann_run
 fann_save
 fann_save_to_fixed
 fann_save_train
 fann_save_train_to_fixed
 fann_scale_input
 fann_scale_input_train_data
 fann_scale_output
 fann_scale_output_train_data
 fann_scale_train
 fann_scale_train_data
 fann_set_activation_function
 fann_set_activation_function_hidden
 fann_set_activation_function_layer
 fann_set_activation_function_output
 fann_set_activation_steepness
 fann_set_activation_steepness_hidden
 fann_set_activation_steepness_layer
 fann_set_activation_steepness_output
 fann_set_bit_fail_limit
 fann_set_callback
 fann_set_cascade_activation_functions
 fann_set_cascade_activation_steepnesses
 fann_set_cascade_candidate_change_fraction
 fann_set_cascade_candidate_limit
 fann_set_cascade_candidate_stagnation_epochs
 fann_set_cascade_max_cand_epochs
 fann_set_cascade_max_out_epochs
 fann_set_cascade_min_cand_epochs
 fann_set_cascade_min_out_epochs
 fann_set_cascade_num_candidate_groups
 fann_set_cascade_output_change_fraction
 fann_set_cascade_output_stagnation_epochs
 fann_set_cascade_weight_multiplier
 fann_set_error_log
 fann_set_input_scaling_params
 fann_set_learning_momentum
 fann_set_learning_rate
 fann_set_output_scaling_params
 fann_set_quickprop_decay
 fann_set_quickprop_mu
 fann_set_rprop_decrease_factor
 fann_set_rprop_delta_max
 fann_set_rprop_delta_min
 fann_set_rprop_delta_zero
 fann_set_rprop_increase_factor
 fann_set_sarprop_step_error_shift
 fann_set_sarprop_step_error_threshold_factor
 fann_set_sarprop_temperature
 fann_set_sarprop_weight_decay_shift
 fann_set_scaling_params
 fann_set_train_error_function
 fann_set_train_stop_function
 fann_set_training_algorithm
 fann_set_user_data
 fann_set_weight
 fann_set_weight_array
 fann_set_weights
 fann_shuffle_train_data
 fann_subset_train_data
 fann_test
 fann_test_data
 fann_train
 fann_train_epoch
 fann_train_on_data
 fann_train_on_file
FANN_EXTERNAL void FANN_API fann_cascadetrain_on_data(
   struct fann *ann,
   struct fann_train_data *data,
   unsigned int max_neurons,
   unsigned int neurons_between_reports,
   float desired_error
)
Trains on an entire dataset, for a period of time using the Cascade2 training algorithm.
FANN_EXTERNAL void FANN_API fann_cascadetrain_on_file(
   struct fann *ann,
   const char *filename,
   unsigned int max_neurons,
   unsigned int neurons_between_reports,
   float desired_error
)
Does the same as fann_cascadetrain_on_data, but reads the training data directly from a file.
FANN_EXTERNAL int FANN_API fann_clear_scaling_params(struct fann *ann)
Clears scaling parameters.
FANN_EXTERNAL struct fann * FANN_API fann_copy(struct fann *ann)
Creates a copy of a fann structure.
FANN_EXTERNAL struct fann *FANN_API fann_create_from_file(
   const char *configuration_file
)
Constructs a backpropagation neural network from a configuration file, which has been saved by fann_save.
FANN_EXTERNAL struct fann *FANN_API fann_create_shortcut(
   unsigned int num_layers,
    ...
)
Creates a standard backpropagation neural network, which is fully connected and which also has shortcut connections.
FANN_EXTERNAL struct fann *FANN_API fann_create_shortcut_array(
   unsigned int num_layers,
   const unsigned int *layers
)
Just like fann_create_shortcut, but with an array of layer sizes instead of individual parameters.
FANN_EXTERNAL struct fann *FANN_API fann_create_sparse(
   float connection_rate,
   unsigned int num_layers,
    ...
)
Creates a standard backpropagation neural network, which is not fully connected.
FANN_EXTERNAL struct fann *FANN_API fann_create_sparse_array(
   float connection_rate,
   unsigned int num_layers,
   const unsigned int *layers
)
Just like fann_create_sparse, but with an array of layer sizes instead of individual parameters.
FANN_EXTERNAL struct fann *FANN_API fann_create_standard(
   unsigned int num_layers,
    ...
)
Creates a standard fully connected backpropagation neural network.
FANN_EXTERNAL struct fann *FANN_API fann_create_standard_array(
   unsigned int num_layers,
   const unsigned int *layers
)
Just like fann_create_standard, but with an array of layer sizes instead of individual parameters.
FANN_EXTERNAL struct fann_train_data * FANN_API fann_create_train(
   unsigned int num_data,
   unsigned int num_input,
   unsigned int num_output
)
Creates an empty training data struct.
FANN_EXTERNAL struct fann_train_data * FANN_API fann_create_train_array(
   unsigned int num_data,
   unsigned int num_input,
   fann_type *input,
   unsigned int num_output,
   fann_type *output
)
input[num_data*num_input] output[num_data*num_output]
FANN_EXTERNAL struct fann_train_data * FANN_API fann_create_train_from_callback(
   unsigned int num_data,
   unsigned int num_input,
   unsigned int num_output,
   void (FANN_API *user_function)( unsigned int, unsigned int, unsigned int, fann_type * , fann_type * )
)
Creates the training data struct from a user supplied function.
FANN_EXTERNAL struct fann_train_data * FANN_API fann_create_train_pointer_array(
   unsigned int num_data,
   unsigned int num_input,
   fann_type **input,
   unsigned int num_output,
   fann_type **output
)
Creates an training data struct and fills it with data from provided arrays of pointer.
FANN_EXTERNAL void FANN_API fann_descale_input(struct fann *ann,
fann_type *input_vector)
Scale data in input vector after getting it from ann based on previously calculated parameters.
FANN_EXTERNAL void FANN_API fann_descale_output(struct fann *ann,
fann_type *output_vector)
Scale data in output vector after getting it from ann based on previously calculated parameters.
FANN_EXTERNAL void FANN_API fann_descale_train(struct fann *ann,
struct fann_train_data *data)
Descale input and output data based on previously calculated parameters.
FANN_EXTERNAL void FANN_API fann_destroy(struct fann *ann)
Destroys the entire network, properly freeing all the associated memory.
FANN_EXTERNAL void FANN_API fann_destroy_train(
   struct fann_train_data *train_data
)
Destructs the training data and properly deallocates all of the associated data.
FANN_EXTERNAL void FANN_API fann_disable_seed_rand()
Disables the automatic random generator seeding that happens in FANN.
FANN_EXTERNAL struct fann_train_data *FANN_API fann_duplicate_train_data(
   struct fann_train_data *data
)
Returns an exact copy of a struct fann_train_data.
FANN_EXTERNAL void FANN_API fann_enable_seed_rand()
Enables the automatic random generator seeding that happens in FANN.
FANN_EXTERNAL enum fann_activationfunc_enum FANN_API fann_get_activation_function(
   struct fann *ann,
   int layer,
   int neuron
)
Get the activation function for neuron number neuron in layer number layer, counting the input layer as layer 0.
FANN_EXTERNAL fann_type FANN_API fann_get_activation_steepness(
   struct fann *ann,
   int layer,
   int neuron
)
Get the activation steepness for neuron number neuron in layer number layer, counting the input layer as layer 0.
FANN_EXTERNAL void FANN_API fann_get_bias_array(struct fann *ann,
unsigned int *bias)
Get the number of bias in each layer in the network.
FANN_EXTERNAL unsigned int FANN_API fann_get_bit_fail(struct fann *ann)
The number of fail bits; means the number of output neurons which differ more than the bit fail limit (see fann_get_bit_fail_limit, fann_set_bit_fail_limit).
FANN_EXTERNAL fann_type FANN_API fann_get_bit_fail_limit(struct fann *ann)
Returns the bit fail limit used during training.
FANN_EXTERNAL enum fann_activationfunc_enum * FANN_API fann_get_cascade_activation_functions(
   struct fann *ann
)
The cascade activation functions array is an array of the different activation functions used by the candidates.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_activation_functions_count(
   struct fann *ann
)
The number of activation functions in the fann_get_cascade_activation_functions array.
FANN_EXTERNAL fann_type * FANN_API fann_get_cascade_activation_steepnesses(
   struct fann *ann
)
The cascade activation steepnesses array is an array of the different activation functions used by the candidates.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_activation_steepnesses_count(
   struct fann *ann
)
The number of activation steepnesses in the fann_get_cascade_activation_functions array.
FANN_EXTERNAL float FANN_API fann_get_cascade_candidate_change_fraction(
   struct fann *ann
)
The cascade candidate change fraction is a number between 0 and 1 determining how large a fraction the fann_get_MSE value should change within fann_get_cascade_candidate_stagnation_epochs during training of the candidate neurons, in order for the training not to stagnate.
FANN_EXTERNAL fann_type FANN_API fann_get_cascade_candidate_limit(
   struct fann *ann
)
The candidate limit is a limit for how much the candidate neuron may be trained.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_candidate_stagnation_epochs(
   struct fann *ann
)
The number of cascade candidate stagnation epochs determines the number of epochs training is allowed to continue without changing the MSE by a fraction of fann_get_cascade_candidate_change_fraction.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_max_cand_epochs(
   struct fann *ann
)
The maximum candidate epochs determines the maximum number of epochs the input connections to the candidates may be trained before adding a new candidate neuron.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_max_out_epochs(
   struct fann *ann
)
The maximum out epochs determines the maximum number of epochs the output connections may be trained after adding a new candidate neuron.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_min_cand_epochs(
   struct fann *ann
)
The minimum candidate epochs determines the minimum number of epochs the input connections to the candidates may be trained before adding a new candidate neuron.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_min_out_epochs(
   struct fann *ann
)
The minimum out epochs determines the minimum number of epochs the output connections must be trained after adding a new candidate neuron.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_num_candidate_groups(
   struct fann *ann
)
The number of candidate groups is the number of groups of identical candidates which will be used during training.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_num_candidates(
   struct fann *ann
)
The number of candidates used during training (calculated by multiplying fann_get_cascade_activation_functions_count, fann_get_cascade_activation_steepnesses_count and fann_get_cascade_num_candidate_groups).
FANN_EXTERNAL float FANN_API fann_get_cascade_output_change_fraction(
   struct fann *ann
)
The cascade output change fraction is a number between 0 and 1 determining how large a fraction the fann_get_MSE value should change within fann_get_cascade_output_stagnation_epochs during training of the output connections, in order for the training not to stagnate.
FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_output_stagnation_epochs(
   struct fann *ann
)
The number of cascade output stagnation epochs determines the number of epochs training is allowed to continue without changing the MSE by a fraction of fann_get_cascade_output_change_fraction.
FANN_EXTERNAL fann_type FANN_API fann_get_cascade_weight_multiplier(
   struct fann *ann
)
The weight multiplier is a parameter which is used to multiply the weights from the candidate neuron before adding the neuron to the neural network.
FANN_EXTERNAL void FANN_API fann_get_connection_array(
   struct fann *ann,
   struct fann_connection *connections
)
Get the connections in the network.
FANN_EXTERNAL float FANN_API fann_get_connection_rate(struct fann *ann)
Get the connection rate used when the network was created
FANN_EXTERNAL unsigned int FANN_API fann_get_decimal_point(struct fann *ann)
Returns the position of the decimal point in the ann.
FANN_EXTERNAL enum fann_errno_enum FANN_API fann_get_errno(
   struct fann_error *errdat
)
Returns the last error number.
FANN_EXTERNAL char *FANN_API fann_get_errstr(struct fann_error *errdat)
Returns the last errstr.
FANN_EXTERNAL void FANN_API fann_get_layer_array(struct fann *ann,
unsigned int *layers)
Get the number of neurons in each layer in the network.
FANN_EXTERNAL float FANN_API fann_get_learning_momentum(struct fann *ann)
Get the learning momentum.
FANN_EXTERNAL float FANN_API fann_get_learning_rate(struct fann *ann)
Return the learning rate.
FANN_EXTERNAL fann_type FANN_API fann_get_max_train_input(
   struct fann_train_data *train_data
)
Get the maximum value of all in the input data
FANN_EXTERNAL fann_type FANN_API fann_get_max_train_output(
   struct fann_train_data *train_data
)
Get the maximum value of all in the output data
FANN_EXTERNAL fann_type FANN_API fann_get_min_train_input(
   struct fann_train_data *train_data
)
Get the minimum value of all in the input data
FANN_EXTERNAL fann_type FANN_API fann_get_min_train_output(
   struct fann_train_data *train_data
)
Get the minimum value of all in the output data
FANN_EXTERNAL float FANN_API fann_get_MSE(struct fann *ann)
Reads the mean square error from the network.
FANN_EXTERNAL unsigned int FANN_API fann_get_multiplier(struct fann *ann)
returns the multiplier that fix point data is multiplied with.
FANN_EXTERNAL enum fann_nettype_enum FANN_API fann_get_network_type(
   struct fann *ann
)
Get the type of neural network it was created as.
FANN_EXTERNAL unsigned int FANN_API fann_get_num_input(struct fann *ann)
Get the number of input neurons.
FANN_EXTERNAL unsigned int FANN_API fann_get_num_layers(struct fann *ann)
Get the number of layers in the network
FANN_EXTERNAL unsigned int FANN_API fann_get_num_output(struct fann *ann)
Get the number of output neurons.
FANN_EXTERNAL float FANN_API fann_get_quickprop_decay(struct fann *ann)
The decay is a small negative valued number which is the factor that the weights should become smaller in each iteration during quickprop training.
FANN_EXTERNAL float FANN_API fann_get_quickprop_mu(struct fann *ann)
The mu factor is used to increase and decrease the step-size during quickprop training.
FANN_EXTERNAL float FANN_API fann_get_rprop_decrease_factor(struct fann *ann)
The decrease factor is a value smaller than 1, which is used to decrease the step-size during RPROP training.
FANN_EXTERNAL float FANN_API fann_get_rprop_delta_max(struct fann *ann)
The maximum step-size is a positive number determining how large the maximum step-size may be.
FANN_EXTERNAL float FANN_API fann_get_rprop_delta_min(struct fann *ann)
The minimum step-size is a small positive number determining how small the minimum step-size may be.
FANN_EXTERNAL float FANN_API fann_get_rprop_delta_zero(struct fann *ann)
The initial step-size is a positive number determining the initial step size.
FANN_EXTERNAL float FANN_API fann_get_rprop_increase_factor(struct fann *ann)
The increase factor is a value larger than 1, which is used to increase the step-size during RPROP training.
FANN_EXTERNAL float FANN_API fann_get_sarprop_step_error_shift(
   struct fann *ann
)
The get sarprop step error shift.
FANN_EXTERNAL float FANN_API fann_get_sarprop_step_error_threshold_factor(
   struct fann *ann
)
The sarprop step error threshold factor.
FANN_EXTERNAL float FANN_API fann_get_sarprop_temperature(struct fann *ann)
The sarprop weight decay shift.
FANN_EXTERNAL float FANN_API fann_get_sarprop_weight_decay_shift(
   struct fann *ann
)
The sarprop weight decay shift.
FANN_EXTERNAL unsigned int FANN_API fann_get_total_connections(
   struct fann *ann
)
Get the total number of connections in the entire network.
FANN_EXTERNAL unsigned int FANN_API fann_get_total_neurons(struct fann *ann)
Get the total number of neurons in the entire network.
FANN_EXTERNAL enum fann_errorfunc_enum FANN_API fann_get_train_error_function(
   struct fann *ann
)
Returns the error function used during training.
FANN_EXTERNAL fann_type * FANN_API fann_get_train_input(
   struct fann_train_data *data,
   unsigned int position
)
Gets the training input data at the given position
FANN_EXTERNAL fann_type * FANN_API fann_get_train_output(
   struct fann_train_data *data,
   unsigned int position
)
Gets the training output data at the given position
FANN_EXTERNAL enum fann_stopfunc_enum FANN_API fann_get_train_stop_function(
   struct fann *ann
)
Returns the the stop function used during training.
FANN_EXTERNAL enum fann_train_enum FANN_API fann_get_training_algorithm(
   struct fann *ann
)
Return the training algorithm as described by fann_train_enum.
FANN_EXTERNAL void * FANN_API fann_get_user_data(struct fann *ann)
Get a pointer to user defined data that was previously set with fann_set_user_data.
FANN_EXTERNAL void FANN_API fann_get_weights(struct fann *ann,
fann_type *weights)
Get all the network weights.
FANN_EXTERNAL void FANN_API fann_init_weights(
   struct fann *ann,
   struct fann_train_data *train_data
)
Initialize the weights using Widrow + Nguyen’s algorithm.
FANN_EXTERNAL unsigned int FANN_API fann_length_train_data(
   struct fann_train_data *data
)
Returns the number of training patterns in the struct fann_train_data.
FANN_EXTERNAL struct fann_train_data *FANN_API fann_merge_train_data(
   struct fann_train_data *data1,
   struct fann_train_data *data2
)
Merges the data from data1 and data2 into a new struct fann_train_data.
FANN_EXTERNAL unsigned int FANN_API fann_num_input_train_data(
   struct fann_train_data *data
)
Returns the number of inputs in each of the training patterns in the struct fann_train_data.
FANN_EXTERNAL unsigned int FANN_API fann_num_output_train_data(
   struct fann_train_data *data
)
Returns the number of outputs in each of the training patterns in the struct fann_train_data.
FANN_EXTERNAL void FANN_API fann_print_connections(struct fann *ann)
Will print the connections of the ann in a compact matrix, for easy viewing of the internals of the ann.
FANN_EXTERNAL void FANN_API fann_print_error(struct fann_error *errdat)
Prints the last error to stderr.
FANN_EXTERNAL void FANN_API fann_print_parameters(struct fann *ann)
Prints all of the parameters and options of the ANN
FANN_EXTERNAL void FANN_API fann_randomize_weights(struct fann *ann,
fann_type min_weight,
fann_type max_weight)
Give each connection a random weight between min_weight and max_weight
FANN_EXTERNAL struct fann_train_data *FANN_API fann_read_train_from_file(
   const char *filename
)
Reads a file that stores training data.
FANN_EXTERNAL void FANN_API fann_reset_errno(struct fann_error *errdat)
Resets the last error number.
FANN_EXTERNAL void FANN_API fann_reset_errstr(struct fann_error *errdat)
Resets the last error string.
FANN_EXTERNAL void FANN_API fann_reset_MSE(struct fann *ann)
Resets the mean square error from the network.
FANN_EXTERNAL fann_type * FANN_API fann_run(struct fann *ann,
fann_type *input)
Will run input through the neural network, returning an array of outputs, the number of which being equal to the number of neurons in the output layer.
FANN_EXTERNAL int FANN_API fann_save(struct fann *ann,
const char *configuration_file)
Save the entire network to a configuration file.
FANN_EXTERNAL int FANN_API fann_save_to_fixed(struct fann *ann,
const char *configuration_file)
Saves the entire network to a configuration file.
FANN_EXTERNAL int FANN_API fann_save_train(struct fann_train_data *data,
const char *filename)
Save the training structure to a file, with the format as specified in fann_read_train_from_file
FANN_EXTERNAL int FANN_API fann_save_train_to_fixed(
   struct fann_train_data *data,
   const char *filename,
   unsigned int decimal_point
)
Saves the training structure to a fixed point data file.
FANN_EXTERNAL void FANN_API fann_scale_input(struct fann *ann,
fann_type *input_vector)
Scale data in input vector before feeding it to ann based on previously calculated parameters.
FANN_EXTERNAL void FANN_API fann_scale_input_train_data(
   struct fann_train_data *train_data,
   fann_type new_min,
   fann_type new_max
)
Scales the inputs in the training data to the specified range.
FANN_EXTERNAL void FANN_API fann_scale_output(struct fann *ann,
fann_type *output_vector)
Scale data in output vector before feeding it to ann based on previously calculated parameters.
FANN_EXTERNAL void FANN_API fann_scale_output_train_data(
   struct fann_train_data *train_data,
   fann_type new_min,
   fann_type new_max
)
Scales the outputs in the training data to the specified range.
FANN_EXTERNAL void FANN_API fann_scale_train(struct fann *ann,
struct fann_train_data *data)
Scale input and output data based on previously calculated parameters.
FANN_EXTERNAL void FANN_API fann_scale_train_data(
   struct fann_train_data *train_data,
   fann_type new_min,
   fann_type new_max
)
Scales the inputs and outputs in the training data to the specified range.
FANN_EXTERNAL void FANN_API fann_set_activation_function(
   struct fann *ann,
   enum fann_activationfunc_enum activation_function,
   int layer,
   int neuron
)
Set the activation function for neuron number neuron in layer number layer, counting the input layer as layer 0.
FANN_EXTERNAL void FANN_API fann_set_activation_function_hidden(
   struct fann *ann,
   enum fann_activationfunc_enum activation_function
)
Set the activation function for all of the hidden layers.
FANN_EXTERNAL void FANN_API fann_set_activation_function_layer(
   struct fann *ann,
   enum fann_activationfunc_enum activation_function,
   int layer
)
Set the activation function for all the neurons in the layer number layer, counting the input layer as layer 0.
FANN_EXTERNAL void FANN_API fann_set_activation_function_output(
   struct fann *ann,
   enum fann_activationfunc_enum activation_function
)
Set the activation function for the output layer.
FANN_EXTERNAL void FANN_API fann_set_activation_steepness(struct fann *ann,
fann_type steepness,
int layer,
int neuron)
Set the activation steepness for neuron number neuron in layer number layer, counting the input layer as layer 0.
FANN_EXTERNAL void FANN_API fann_set_activation_steepness_hidden(
   struct fann *ann,
   fann_type steepness
)
Set the steepness of the activation steepness in all of the hidden layers.
FANN_EXTERNAL void FANN_API fann_set_activation_steepness_layer(
   struct fann *ann,
   fann_type steepness,
   int layer
)
Set the activation steepness for all of the neurons in layer number layer, counting the input layer as layer 0.
FANN_EXTERNAL void FANN_API fann_set_activation_steepness_output(
   struct fann *ann,
   fann_type steepness
)
Set the steepness of the activation steepness in the output layer.
FANN_EXTERNAL void FANN_API fann_set_bit_fail_limit(struct fann *ann,
fann_type bit_fail_limit)
Set the bit fail limit used during training.
FANN_EXTERNAL void FANN_API fann_set_callback(struct fann *ann,
fann_callback_type callback)
Sets the callback function for use during training.
FANN_EXTERNAL void FANN_API fann_set_cascade_activation_functions(
   struct fann *ann,
   enum fann_activationfunc_enum *cascade_activation_functions,
   unsigned int cascade_activation_functions_count
)
Sets the array of cascade candidate activation functions.
FANN_EXTERNAL void FANN_API fann_set_cascade_activation_steepnesses(
   struct fann *ann,
   fann_type *cascade_activation_steepnesses,
   unsigned int cascade_activation_steepnesses_count
)
Sets the array of cascade candidate activation steepnesses.
FANN_EXTERNAL void FANN_API fann_set_cascade_candidate_change_fraction(
   struct fann *ann,
   float cascade_candidate_change_fraction
)
Sets the cascade candidate change fraction.
FANN_EXTERNAL void FANN_API fann_set_cascade_candidate_limit(
   struct fann *ann,
   fann_type cascade_candidate_limit
)
Sets the candidate limit.
FANN_EXTERNAL void FANN_API fann_set_cascade_candidate_stagnation_epochs(
   struct fann *ann,
   unsigned int cascade_candidate_stagnation_epochs
)
Sets the number of cascade candidate stagnation epochs.
FANN_EXTERNAL void FANN_API fann_set_cascade_max_cand_epochs(
   struct fann *ann,
   unsigned int cascade_max_cand_epochs
)
Sets the max candidate epochs.
FANN_EXTERNAL void FANN_API fann_set_cascade_max_out_epochs(
   struct fann *ann,
   unsigned int cascade_max_out_epochs
)
Sets the maximum out epochs.
FANN_EXTERNAL void FANN_API fann_set_cascade_min_cand_epochs(
   struct fann *ann,
   unsigned int cascade_min_cand_epochs
)
Sets the min candidate epochs.
FANN_EXTERNAL void FANN_API fann_set_cascade_min_out_epochs(
   struct fann *ann,
   unsigned int cascade_min_out_epochs
)
Sets the minimum out epochs.
FANN_EXTERNAL void FANN_API fann_set_cascade_num_candidate_groups(
   struct fann *ann,
   unsigned int cascade_num_candidate_groups
)
Sets the number of candidate groups.
FANN_EXTERNAL void FANN_API fann_set_cascade_output_change_fraction(
   struct fann *ann,
   float cascade_output_change_fraction
)
Sets the cascade output change fraction.
FANN_EXTERNAL void FANN_API fann_set_cascade_output_stagnation_epochs(
   struct fann *ann,
   unsigned int cascade_output_stagnation_epochs
)
Sets the number of cascade output stagnation epochs.
FANN_EXTERNAL void FANN_API fann_set_cascade_weight_multiplier(
   struct fann *ann,
   fann_type cascade_weight_multiplier
)
Sets the weight multiplier.
FANN_EXTERNAL void FANN_API fann_set_error_log(struct fann_error *errdat,
FILE *log_file)
Change where errors are logged to.
FANN_EXTERNAL int FANN_API fann_set_input_scaling_params(
   struct fann *ann,
   const struct fann_train_data *data,
   float new_input_min,
   float new_input_max
)
Calculate input scaling parameters for future use based on training data.
FANN_EXTERNAL void FANN_API fann_set_learning_momentum(struct fann *ann,
float learning_momentum)
Set the learning momentum.
FANN_EXTERNAL void FANN_API fann_set_learning_rate(struct fann *ann,
float learning_rate)
Set the learning rate.
FANN_EXTERNAL int FANN_API fann_set_output_scaling_params(
   struct fann *ann,
   const struct fann_train_data *data,
   float new_output_min,
   float new_output_max
)
Calculate output scaling parameters for future use based on training data.
FANN_EXTERNAL void FANN_API fann_set_quickprop_decay(struct fann *ann,
float quickprop_decay)
Sets the quickprop decay factor.
FANN_EXTERNAL void FANN_API fann_set_quickprop_mu(struct fann *ann,
float quickprop_mu)
Sets the quickprop mu factor.
FANN_EXTERNAL void FANN_API fann_set_rprop_decrease_factor(
   struct fann *ann,
   float rprop_decrease_factor
)
The decrease factor is a value smaller than 1, which is used to decrease the step-size during RPROP training.
FANN_EXTERNAL void FANN_API fann_set_rprop_delta_max(struct fann *ann,
float rprop_delta_max)
The maximum step-size is a positive number determining how large the maximum step-size may be.
FANN_EXTERNAL void FANN_API fann_set_rprop_delta_min(struct fann *ann,
float rprop_delta_min)
The minimum step-size is a small positive number determining how small the minimum step-size may be.
FANN_EXTERNAL void FANN_API fann_set_rprop_delta_zero(struct fann *ann,
float rprop_delta_max)
The initial step-size is a positive number determining the initial step size.
FANN_EXTERNAL void FANN_API fann_set_rprop_increase_factor(
   struct fann *ann,
   float rprop_increase_factor
)
The increase factor used during RPROP training.
FANN_EXTERNAL void FANN_API fann_set_sarprop_step_error_shift(
   struct fann *ann,
   float sarprop_step_error_shift
)
Set the sarprop step error shift.
FANN_EXTERNAL void FANN_API fann_set_sarprop_step_error_threshold_factor(
   struct fann *ann,
   float sarprop_step_error_threshold_factor
)
Set the sarprop step error threshold factor.
FANN_EXTERNAL void FANN_API fann_set_sarprop_temperature(
   struct fann *ann,
   float sarprop_temperature
)
Set the sarprop_temperature.
FANN_EXTERNAL void FANN_API fann_set_sarprop_weight_decay_shift(
   struct fann *ann,
   float sarprop_weight_decay_shift
)
Set the sarprop weight decay shift.
FANN_EXTERNAL int FANN_API fann_set_scaling_params(
   struct fann *ann,
   const struct fann_train_data *data,
   float new_input_min,
   float new_input_max,
   float new_output_min,
   float new_output_max
)
Calculate input and output scaling parameters for future use based on training data.
FANN_EXTERNAL void FANN_API fann_set_train_error_function(
   struct fann *ann,
   enum fann_errorfunc_enum train_error_function
)
Set the error function used during training.
FANN_EXTERNAL void FANN_API fann_set_train_stop_function(
   struct fann *ann,
   enum fann_stopfunc_enum train_stop_function
)
Set the stop function used during training.
FANN_EXTERNAL void FANN_API fann_set_training_algorithm(
   struct fann *ann,
   enum fann_train_enum training_algorithm
)
Set the training algorithm.
FANN_EXTERNAL void FANN_API fann_set_user_data(struct fann *ann,
void *user_data)
Store a pointer to user defined data.
FANN_EXTERNAL void FANN_API fann_set_weight(struct fann *ann,
unsigned int from_neuron,
unsigned int to_neuron,
fann_type weight)
Set a connection in the network.
FANN_EXTERNAL void FANN_API fann_set_weight_array(
   struct fann *ann,
   struct fann_connection *connections,
   unsigned int num_connections
)
Set connections in the network.
FANN_EXTERNAL void FANN_API fann_set_weights(struct fann *ann,
fann_type *weights)
Set network weights.
FANN_EXTERNAL void FANN_API fann_shuffle_train_data(
   struct fann_train_data *train_data
)
Shuffles training data, randomizing the order.
FANN_EXTERNAL struct fann_train_data *FANN_API fann_subset_train_data(
   struct fann_train_data *data,
   unsigned int pos,
   unsigned int length
)
Returns an copy of a subset of the struct fann_train_data, starting at position pos and length elements forward.
FANN_EXTERNAL fann_type * FANN_API fann_test(struct fann *ann,
fann_type *input,
fann_type *desired_output)
Test with a set of inputs, and a set of desired outputs.
FANN_EXTERNAL float FANN_API fann_test_data(struct fann *ann,
struct fann_train_data *data)
Test a set of training data and calculates the MSE for the training data.
FANN_EXTERNAL void FANN_API fann_train(struct fann *ann,
fann_type *input,
fann_type *desired_output)
Train one iteration with a set of inputs, and a set of desired outputs.
FANN_EXTERNAL float FANN_API fann_train_epoch(struct fann *ann,
struct fann_train_data *data)
Train one epoch with a set of training data.
FANN_EXTERNAL void FANN_API fann_train_on_data(
   struct fann *ann,
   struct fann_train_data *data,
   unsigned int max_epochs,
   unsigned int epochs_between_reports,
   float desired_error
)
Trains on an entire dataset, for a period of time.
FANN_EXTERNAL void FANN_API fann_train_on_file(
   struct fann *ann,
   const char *filename,
   unsigned int max_epochs,
   unsigned int epochs_between_reports,
   float desired_error
)
Does the same as fann_train_on_data, but reads the training data directly from a file.
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