fann_train_on_file

(PECL fann >= 1.0.0)

fann_train_on_file — Trains on an entire dataset, which is read from file, for a period of time

Description

fann_train_on_file(
resource $ann,
string $filename,
int $max_epochs,
int $epochs_between_reports,
float $desired_error
): bool

Trains on an entire dataset, which is read from file, for a period of time.

This training uses the training algorithm chosen by fann_set_training_algorithm() and the parameters set for these training algorithms.

Parameters

ann: Neural network resource .
filename: The file containing train data
max_epochs: The maximum number of epochs the training should continue
epochs_between_reports: The number of epochs between calling a user function. A value of zero means that user function is not called.
desired_error: The desired fann_get_MSE() or fann_get_bit_fail() , depending on the stop function chosen by fann_set_train_stop_function()

Return Values

Returns true on success, or false otherwise.

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User Contributed Notes 1 note

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geekgirljoy at gmail dot com ¶

6 years ago

Training File (xor.data):
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<?php
$num_input = 2;
$num_output = 1;
$num_layers = 3;
$num_neurons_hidden = 3;
$desired_error = 0.001;
$max_epochs = 500000;
$epochs_between_reports = 1000;
$training_data = dirname(__FILE__) . "/xor.data"; // training data file
$ann_save_file = dirname(__FILE__) . "/xor_float.net"; // training data file

// Create ANN object using
$ann = fann_create_standard($num_layers, $num_input, $num_neurons_hidden, $num_output);

if ($ann) {
 
 // Configure the ANN Activation Function 
 fann_set_activation_function_hidden($ann, FANN_SIGMOID_SYMMETRIC);
 fann_set_activation_function_output($ann, FANN_SIGMOID_SYMMETRIC);
 
 // Try to train using fann_train_on_file()
 if (fann_train_on_file($ann, $training_data, $max_epochs, $epochs_between_reports, $desired_error)){
 echo 'xor trained.' . PHP_EOL);
 }
 
 // Try to save
 if (fann_save($ann, $ann_save_file)){
 echo 'xor saved.' . PHP_EOL);
 }
 
 // Destroy the $ann object
 fann_destroy($ann);
}
?>