fann_train_epoch

    (PECL fann >= 1.0.0)

    fann_train_epoch — 使用一组训练数据训练一个周期。

    说明

    fann_train_epoch(resource $ann, resource $data): float

    使用保存在 data 中训练数据训练一个周期。一个训练周期表示所有的训练数据正好使用了一次。

    这个函数将会返回在其实际计算之前或当中被计算的 MSE 错误。但是因为计算需要再次走一遍整个训练集，所有训练周期之后的不是真正的 MSE。 在训练中使用这个值是绰绰有余的。

    该函数使用的是被 fann_set_training_algorithm() 函数选中的训练算法。

    参数

    ann

    神经网络 资源。

    data

    神经网络训练数据 资源。

    返回值

    成功，则返回 MSE, 错误则返回 false .

    参见

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    geekgirljoy at gmail dot com
    6 years ago
    This code demonstrates training XOR using fann_train_epoch and will let you watch the training process by observing a psudo MSE (mean squared error).

    Other training functions: fann_train_on_data, fann_train_on_file, fann_train.

    fann_train_epoch is useful when you want to observe the ANN while it is training and perhaps save snapshots or compare competing networks during training.

    fann_train_epoch is different from fann_train in that it takes a data resource (training file) whereas fann_train takes an array of inputs and a separate array of outputs so use fann_train_epoch for observing training on data files (callback training resources) and use fann_train when observing manually specified data.

    Example code:

    <?php
    $num_input     = 2;
    $num_output = 1;
    $num_layers = 3;
    $num_neurons_hidden = 3;
    $desired_error = 0.0001;
    $max_epochs = 500000;
    $current_epoch = 0;
    $epochs_between_saves = 100; // Minimum number of epochs between saves
    $epochs_since_last_save = 0;
    $filename = dirname(__FILE__) . "/xor.data";

    // Initialize psudo mse (mean squared error) to a number greater than the desired_error
    // this is what the network is trying to minimize.
    $psudo_mse_result = $desired_error * 10000; // 1
    $best_mse = $psudo_mse_result; // keep the last best seen MSE network score here

    // Initialize ANN
    $ann = fann_create_standard($num_layers, $num_input, $num_neurons_hidden, $num_output);

    if (    $ann) {
    echo     'Training ANN... ' . PHP_EOL;

    // Configure the ANN
    fann_set_training_algorithm ($ann , FANN_TRAIN_BATCH);
    fann_set_activation_function_hidden($ann, FANN_SIGMOID_SYMMETRIC);
    fann_set_activation_function_output($ann, FANN_SIGMOID_SYMMETRIC);

    // Read training data
    $train_data = fann_read_train_from_file($filename);


    // Check if psudo_mse_result is greater than our desired_error
    // if so keep training so long as we are also under max_epochs
    while(($psudo_mse_result > $desired_error) && ($current_epoch <= $max_epochs)){
    $current_epoch++;
    $epochs_since_last_save++;

    // See: http://php.net/manual/en/function.fann-train-epoch.php
    // Train one epoch with the training data stored in data.
    //
    // One epoch is where all of the training data is considered
    // exactly once.
    //
    // This function returns the MSE error as it is calculated
    // either before or during the actual training. This is not the
    // actual MSE after the training epoch, but since calculating this
    // will require to go through the entire training set once more.
    // It is more than adequate to use this value during training.
    $psudo_mse_result = fann_train_epoch ($ann , $train_data );
    echo     'Epoch ' . $current_epoch . ' : ' . $psudo_mse_result . PHP_EOL; // report


    // If we haven't saved the ANN in a while...
    // and the current network is better then the previous best network
    // as defined by the current MSE being less than the last best MSE
    // Save it!
    if(($epochs_since_last_save >= $epochs_between_saves) && ($psudo_mse_result < $best_mse)){

    $best_mse = $psudo_mse_result; // we have a new best_mse

    // Save a Snapshot of the ANN
    fann_save($ann, dirname(__FILE__) . "/xor.net");
    echo     'Saved ANN.' . PHP_EOL; // report the save
    $epochs_since_last_save = 0; // reset the count
    }

    }     // While we're training

    echo 'Training Complete! Saving Final Network.' . PHP_EOL;

    // Save the final network
    fann_save($ann, dirname(__FILE__) . "/xor.net");
    fann_destroy($ann); // free memory
    }
    echo     'All Done!' . PHP_EOL;
    ?>
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