tf.keras.losses.MeanSquaredLogarithmicError

Computes the mean squared logarithmic error between y_true & y_pred.

Inherits From: Loss

tf.keras.losses.MeanSquaredLogarithmicError(
    reduction='sum_over_batch_size',
    name='mean_squared_logarithmic_error'
)

loss = mean(square(log(y_true + 1) - log(y_pred + 1)))

Args
`reduction`	Type of reduction to apply to the loss. In almost all cases this should be `"sum_over_batch_size"`. Supported options are `"sum"`, `"sum_over_batch_size"` or `None`.
`name`	Optional name for the loss instance.

Methods

call(
    y_true, y_pred
)

@classmethod
from_config(
    config
)

get_config()

__call__(
    y_true, y_pred, sample_weight=None
)

Call self as a function.

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Last updated 2024-06-07 UTC.