MeanAbsoluteError

Calcula la media de la diferencia absoluta entre etiquetas y predicciones.

loss = abs(labels - predictions)

Uso independiente:

    Operand<TFloat32> labels =
        tf.constant(new float[][] { {0.f, 1.f}, {0.f, 0.f} });
    Operand<TFloat32> predictions =
        tf.constant(new float[][] { {1.f, 1.f}, {1.f, 0.f} });
    MeanAbsoluteError mae = new MeanAbsoluteError(tf);
    Operand<TFloat32> result = mae.call(labels, predictions);
    // produces 0.5f
 

Llamando con el peso de la muestra:

    Operand<TFloat32> sampleWeight = tf.constant(new float[] {0.7f, 0.3f});
    Operand<TFloat32> result = mae.call(labels, predictions, sampleWeight);
    // produces 0.25f
 

Usando el tipo de reducción SUM :

    MeanAbsoluteError mae = new MeanAbsoluteError(tf, Reduction.SUM);
    Operand<TFloat32> result = mae.call(labels, predictions);
    // produces 1.0f
 

Usando NONE tipo de reducción:

    MeanAbsoluteError mae = new MeanAbsoluteError(tf, Reduction.NONE);
    Operand<TFloat32> result = mae.call(labels, predictions);
    // produces [0.5f, 0.5f]