tf.keras.losses.MAPE | TensorFlow v2.16.1 (original) (raw)
tf.keras.losses.MAPE
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Computes the mean absolute percentage error between y_true & y_pred.
View aliases
Main aliases
tf.keras.losses.mape, tf.keras.metrics.MAPE, tf.keras.metrics.mape
tf.keras.losses.MAPE(
y_true, y_pred
)
Formula:
loss = 100 * mean(abs((y_true - y_pred) / y_true), axis=-1)
Division by zero is prevented by dividing by maximum(y_true, epsilon)where epsilon = keras.backend.epsilon()(default to 1e-7).
| Args | |
|---|---|
| y_true | Ground truth values with shape = [batch_size, d0, .. dN]. |
| y_pred | The predicted values with shape = [batch_size, d0, .. dN]. |
| Returns |
|---|
| Mean absolute percentage error values with shape = [batch_size, d0, .. dN-1]. |
Example:
y_true = np.random.random(size=(2, 3))
y_pred = np.random.random(size=(2, 3))
loss = keras.losses.mean_absolute_percentage_error(y_true, y_pred)
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Last updated 2024-06-07 UTC.