smooth.ES.loss_value

property ES.loss_value: float

$lossValue).

The final value of the loss function after optimization. Lower values indicate better fit (for most loss functions).

Returns:

The minimized loss function value from the optimization process.

Return type:

float

Raises:

ValueError – If the model has not been fitted yet.

See also

loss

The loss function type used

loglik

Log-likelihood value

Examples

>>> model = ADAM(model="AAN", loss="MSE")
>>> model.fit(y)
>>> print(f"MSE: {model.loss_value:.4f}")

Type:

Optimized loss/cost function value (R