(PECL fann >= 1.0.0) Get the connection rate used when the network was created float fann_get_connection_rate ( resource $ann ) Get the connection rate used when the network was created. Parameters: ann Neural network resource. Returns: The connection rate used when the network was created, or FALSE on error.

(PECL fann >= 1.0.0) Get connections in the network array fann_get_connection_array ( resource $ann ) Get connections in the network. Parameters: ann Neural network resource. Returns: An array of connections in the network

(PECL fann >= 1.0.0) Returns the weight multiplier float fann_get_cascade_weight_multiplier ( resource $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. This parameter is usually between 0 and 1, and is used to make the training a bit less aggressive. The default weight multiplier is 0.4. Parameters

(PECL fann >= 1.0.0) Returns the number of cascade output stagnation epochs int fann_get_cascade_output_stagnation_epochs ( resource $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(). See more info about this parameter in fann_get_cascade_output_change_fraction(). The

(PECL fann >= 1.0.0) Returns the cascade output change fraction float fann_get_cascade_output_change_fraction ( resource $ann ) The cascade output change fraction is a number between 0 and 1 determining how large a fraction of 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. If the training stagna

(PECL fann >= 1.0.0) Returns the number of candidates used during training int fann_get_cascade_num_candidates ( resource $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()). The actual candidates is defined by the fann_get_cascade_activation_functions()

(PECL fann >= 1.0.0) Returns the number of candidate groups int fann_get_cascade_num_candidate_groups ( resource $ann ) The number of candidate groups is the number of groups of identical candidates which will be used during training. This number can be used to have more candidates without having to define new parameters for the candidates. See fann_get_cascade_num_candidates() for a description of which candidate neu

(PECL fann >= 1.0.0) Returns the minimum out epochs int fann_get_cascade_min_out_epochs ( resource $ann ) The minimum out epochs determines the minimum number of epochs the output connections must be trained after adding a new candidate neuron. The default min out epochs is 50. Parameters: ann Neural network resource. Returns: The minimum out

(PECL fann >= 1.0.0) Returns the minimum candidate epochs int fann_get_cascade_min_cand_epochs ( resource $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. The default min candidate epochs is 50. Parameters: ann Neural network resource.

(PECL fann >= 1.0.0) Returns the maximum out epochs int fann_get_cascade_max_out_epochs ( resource $ann ) The maximum out epochs determines the maximum number of epochs the output connections may be trained after adding a new candidate neuron. The default max out epochs is 150. Parameters: ann Neural network resource. Returns: The maximum out