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

    Опис

    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.

    Параметри

    ann

    Ресурс (resource) нейронної мережі.

    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()

    Значення, що повертаються

    Повертає true у разі успіху або false у разі невдачі.

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    User Contributed Notes 1 note

    up
    1
    geekgirljoy at gmail dot com
    6 years ago
    Training File (xor.data):
    4 2 1
    -1 -1
    -1
    -1 1
    1
    1 -1
    1
    1 1
    -1

    <?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);
    }
    ?>
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