(PECL fann >= 1.0.0) Sets the initial step-size bool fann_set_rprop_delta_zero ( resource $ann, float $rprop_delta_zero ) The initial step-size is a positive number determining the initial step size. Parameters: ann Neural network resource. rprop_delta_zero The initial step-size. Returns: Returns TRUE on succes

(PECL fann >= 1.0.0) Sets the minimum step-size bool fann_set_rprop_delta_min ( resource $ann, float $rprop_delta_min ) The minimum step-size is a small positive number determining how small the minimum step-size may be. Parameters: ann Neural network resource. rprop_delta_min The minimum step-size. Returns: Re

(PECL fann >= 1.0.0) Sets the maximum step-size bool fann_set_rprop_delta_max ( resource $ann, float $rprop_delta_max ) The maximum step-size is a positive number determining how large the maximum step-size may be. Parameters: ann Neural network resource. rprop_delta_max The maximum step-size. Returns: Returns

(PECL fann >= 1.0.0) Sets the decrease factor used during RPROP training bool fann_set_rprop_decrease_factor ( resource $ann, float $rprop_decrease_factor ) Sets the decrease factor used during RPROP training. Parameters: ann Neural network resource. rprop_decrease_factor The decrease factor. Returns: Returns T

(PECL fann >= 1.0.0) Sets the quickprop mu factor bool fann_set_quickprop_mu ( resource $ann, float $quickprop_mu ) Sets the quickprop mu factor. Parameters: ann Neural network resource. quickprop_mu The mu factor. Returns: Returns TRUE on success, or FALSE otherwise.

(PECL fann >= 1.0.0) Sets the quickprop decay factor bool fann_set_quickprop_decay ( resource $ann, float $quickprop_decay ) Sets the quickprop decay factor. Parameters: ann Neural network resource. quickprop_decay The quickprop decay factor. Returns: Returns TRUE on success, or FALSE otherwise.

(PECL fann >= 1.0.0) Calculate output scaling parameters for future use based on training data bool fann_set_output_scaling_params ( resource $ann, resource $train_data, float $new_output_min, float $new_output_max ) Calculate output scaling parameters for future use based on training data. Parameters: ann Neural network resource. train_data

(PECL fann >= 1.0.0) Sets the learning rate bool fann_set_learning_rate ( resource $ann, float $learning_rate ) Sets the learning rate. More info available in fann_get_learning_rate(). Parameters: ann Neural network resource. learning_rate The learning rate. Returns: Returns TRUE on success, or FALSE otherwis

(PECL fann >= 1.0.0) Sets the learning momentum bool fann_set_learning_momentum ( resource $ann, float $learning_momentum ) Sets the learning momentum. More info available in fann_get_learning_momentum(). Parameters: ann Neural network resource. learning_momentum The learning momentum. Returns: Returns TRUE o

(PECL fann >= 1.0.0) Calculate input scaling parameters for future use based on training data bool fann_set_input_scaling_params ( resource $ann, resource $train_data, float $new_input_min, float $new_input_max ) Calculate input scaling parameters for future use based on training data. Parameters: ann Neural network resource. train_data