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FANN (Fast Artificial Neural Network)
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JavaScript入門&応用&リファレンスなら「JavaScriptist」
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はじめに
その他の基本モジュール
PHP Manual
FANN (Fast Artificial Neural Network)
はじめに
インストール/設定
要件
インストール手順
実行時設定
リソース型
定義済み定数
例
XOR training
Fann 関数
fann_cascadetrain_on_data
? Trains on an entire dataset, for a period of time using the Cascade2 training algorithm
fann_cascadetrain_on_file
? Trains on an entire dataset read from file, for a period of time using the Cascade2 training algorithm.
fann_clear_scaling_params
? Clears scaling parameters
fann_copy
? Creates a copy of a fann structure
fann_create_from_file
? Constructs a backpropagation neural network from a configuration file
fann_create_shortcut_array
? Creates a standard backpropagation neural network which is not fully connectected and has shortcut connections
fann_create_shortcut
? Creates a standard backpropagation neural network which is not fully connectected and has shortcut connections
fann_create_sparse_array
? Creates a standard backpropagation neural network, which is not fully connected using an array of layer sizes
fann_create_sparse
? Creates a standard backpropagation neural network, which is not fully connected
fann_create_standard_array
? Creates a standard fully connected backpropagation neural network using an array of layer sizes
fann_create_standard
? Creates a standard fully connected backpropagation neural network
fann_create_train_from_callback
? Creates the training data struct from a user supplied function
fann_create_train
? Creates an empty training data struct
fann_descale_input
? Scale data in input vector after get it from ann based on previously calculated parameters
fann_descale_output
? Scale data in output vector after get it from ann based on previously calculated parameters
fann_descale_train
? Descale input and output data based on previously calculated parameters
fann_destroy_train
? Destructs the training data
fann_destroy
? Destroys the entire network and properly freeing all the associated memory
fann_duplicate_train_data
? Returns an exact copy of a fann train data
fann_get_activation_function
? Returns the activation function
fann_get_activation_steepness
? Returns the activation steepness for supplied neuron and layer number
fann_get_bias_array
? Get the number of bias in each layer in the network
fann_get_bit_fail_limit
? Returns the bit fail limit used during training
fann_get_bit_fail
? The number of fail bits
fann_get_cascade_activation_functions_count
? Returns the number of cascade activation functions
fann_get_cascade_activation_functions
? Returns the cascade activation functions
fann_get_cascade_activation_steepnesses_count
? The number of activation steepnesses
fann_get_cascade_activation_steepnesses
? Returns the cascade activation steepnesses
fann_get_cascade_candidate_change_fraction
? Returns the cascade candidate change fraction
fann_get_cascade_candidate_limit
? Return the candidate limit
fann_get_cascade_candidate_stagnation_epochs
? Returns the number of cascade candidate stagnation epochs
fann_get_cascade_max_cand_epochs
? Returns the maximum candidate epochs
fann_get_cascade_max_out_epochs
? Returns the maximum out epochs
fann_get_cascade_min_cand_epochs
? Returns the minimum candidate epochs
fann_get_cascade_min_out_epochs
? Returns the minimum out epochs
fann_get_cascade_num_candidate_groups
? Returns the number of candidate groups
fann_get_cascade_num_candidates
? Returns the number of candidates used during training
fann_get_cascade_output_change_fraction
? Returns the cascade output change fraction
fann_get_cascade_output_stagnation_epochs
? Returns the number of cascade output stagnation epochs
fann_get_cascade_weight_multiplier
? Returns the weight multiplier
fann_get_connection_array
? Get connections in the network
fann_get_connection_rate
? Get the connection rate used when the network was created
fann_get_errno
? Returns the last error number
fann_get_errstr
? Returns the last errstr
fann_get_layer_array
? Get the number of neurons in each layer in the network
fann_get_learning_momentum
? Returns the learning momentum
fann_get_learning_rate
? Returns the learning rate
fann_get_MSE
? Reads the mean square error from the network
fann_get_network_type
? Get the type of neural network it was created as
fann_get_num_input
? Get the number of input neurons
fann_get_num_layers
? Get the number of layers in the neural network
fann_get_num_output
? Get the number of output neurons
fann_get_quickprop_decay
? Returns the decay which is a factor that weights should decrease in each iteration during quickprop training
fann_get_quickprop_mu
? Returns the mu factor
fann_get_rprop_decrease_factor
? Returns the increase factor used during RPROP training
fann_get_rprop_delta_max
? Returns the maximum step-size
fann_get_rprop_delta_min
? Returns the minimum step-size
fann_get_rprop_delta_zero
? Returns the initial step-size
fann_get_rprop_increase_factor
? Returns the increase factor used during RPROP training
fann_get_sarprop_step_error_shift
? Returns the sarprop step error shift
fann_get_sarprop_step_error_threshold_factor
? Returns the sarprop step error threshold factor
fann_get_sarprop_temperature
? Returns the sarprop temperature
fann_get_sarprop_weight_decay_shift
? Returns the sarprop weight decay shift
fann_get_total_connections
? Get the total number of connections in the entire network
fann_get_total_neurons
? Get the total number of neurons in the entire network
fann_get_train_error_function
? Returns the error function used during training
fann_get_train_stop_function
? Returns the stop function used during training
fann_get_training_algorithm
? Returns the training algorithm
fann_init_weights
? Initialize the weights using Widrow + Nguyen’s algorithm
fann_length_train_data
? Returns the number of training patterns in the train data
fann_merge_train_data
? Merges the train data
fann_num_input_train_data
? Returns the number of inputs in each of the training patterns in the train data
fann_num_output_train_data
? Returns the number of outputs in each of the training patterns in the train data
fann_print_error
? Prints the error string
fann_randomize_weights
? Give each connection a random weight between min_weight and max_weight
fann_read_train_from_file
? Reads a file that stores training data
fann_reset_errno
? Resets the last error number
fann_reset_errstr
? Resets the last error string
fann_reset_MSE
? Resets the mean square error from the network
fann_run
? Will run input through the neural network
fann_save_train
? Save the training structure to a file
fann_save
? Saves the entire network to a configuration file
fann_scale_input_train_data
? Scales the inputs in the training data to the specified range
fann_scale_input
? Scale data in input vector before feed it to ann based on previously calculated parameters
fann_scale_output_train_data
? Scales the outputs in the training data to the specified range
fann_scale_output
? Scale data in output vector before feed it to ann based on previously calculated parameters
fann_scale_train_data
? Scales the inputs and outputs in the training data to the specified range
fann_scale_train
? Scale input and output data based on previously calculated parameters
fann_set_activation_function_hidden
? Sets the activation function for all of the hidden layers
fann_set_activation_function_layer
? Sets the activation function for all the neurons in the supplied layer.
fann_set_activation_function_output
? Sets the activation function for the output layer
fann_set_activation_function
? Sets the activation function for supplied neuron and layer
fann_set_activation_steepness_hidden
? Sets the steepness of the activation steepness for all neurons in the all hidden layers
fann_set_activation_steepness_layer
? Sets the activation steepness for all of the neurons in the supplied layer number
fann_set_activation_steepness_output
? Sets the steepness of the activation steepness in the output layer
fann_set_activation_steepness
? Sets the activation steepness for supplied neuron and layer number
fann_set_bit_fail_limit
? Set the bit fail limit used during training
fann_set_callback
? Sets the callback function for use during training
fann_set_cascade_activation_functions
? Sets the array of cascade candidate activation functions
fann_set_cascade_activation_steepnesses
? Sets the array of cascade candidate activation steepnesses
fann_set_cascade_candidate_change_fraction
? Sets the cascade candidate change fraction
fann_set_cascade_candidate_limit
? Sets the candidate limit
fann_set_cascade_candidate_stagnation_epochs
? Sets the number of cascade candidate stagnation epochs
fann_set_cascade_max_cand_epochs
? Sets the max candidate epochs
fann_set_cascade_max_out_epochs
? Sets the maximum out epochs
fann_set_cascade_min_cand_epochs
? Sets the min candidate epochs
fann_set_cascade_min_out_epochs
? Sets the minimum out epochs
fann_set_cascade_num_candidate_groups
? Sets the number of candidate groups
fann_set_cascade_output_change_fraction
? Sets the cascade output change fraction
fann_set_cascade_output_stagnation_epochs
? Sets the number of cascade output stagnation epochs
fann_set_cascade_weight_multiplier
? Sets the weight multiplier
fann_set_error_log
? Sets where the errors are logged to
fann_set_input_scaling_params
? Calculate input scaling parameters for future use based on training data
fann_set_learning_momentum
? Sets the learning momentum
fann_set_learning_rate
? Sets the learning rate
fann_set_output_scaling_params
? Calculate output scaling parameters for future use based on training data
fann_set_quickprop_decay
? Sets the quickprop decay factor
fann_set_quickprop_mu
? Sets the quickprop mu factor
fann_set_rprop_decrease_factor
? Sets the decrease factor used during RPROP training
fann_set_rprop_delta_max
? Sets the maximum step-size
fann_set_rprop_delta_min
? Sets the minimum step-size
fann_set_rprop_delta_zero
? Sets the initial step-size
fann_set_rprop_increase_factor
? Sets the increase factor used during RPROP training
fann_set_sarprop_step_error_shift
? Sets the sarprop step error shift
fann_set_sarprop_step_error_threshold_factor
? Sets the sarprop step error threshold factor
fann_set_sarprop_temperature
? Sets the sarprop temperature
fann_set_sarprop_weight_decay_shift
? Sets the sarprop weight decay shift
fann_set_scaling_params
? Calculate input and output scaling parameters for future use based on training data
fann_set_train_error_function
? Sets the error function used during training
fann_set_train_stop_function
? Sets the stop function used during training
fann_set_training_algorithm
? Sets the training algorithm
fann_set_weight_array
? Set connections in the network
fann_set_weight
? Set a connection in the network
fann_shuffle_train_data
? Shuffles training data, randomizing the order
fann_subset_train_data
? Returns an copy of a subset of the train data
fann_test_data
? Test a set of training data and calculates the MSE for the training data
fann_test
? Test with a set of inputs, and a set of desired outputs
fann_train_epoch
? Train one epoch with a set of training data
fann_train_on_data
? Trains on an entire dataset for a period of time
fann_train_on_file
? Trains on an entire dataset, which is read from file, for a period of time
fann_train
? Train one iteration with a set of inputs, and a set of desired outputs
FANNConnection
? The FANNConnection class
FANNConnection::__construct
? The connection constructor
FANNConnection::getFromNeuron
? Returns the postions of starting neuron.
FANNConnection::getToNeuron
? Returns the postions of terminating neuron
FANNConnection::getWeight
? Returns the connection weight
FANNConnection::setWeight
? Sets the connections weight
geoip_time_zone_by_country_and_region
はじめに
その他の基本モジュール
PHP Manual
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