Quantile¶

Quantile loss.

Parameters¶

• alpha – defaults to 0.5

Desired quantile to attain.

Examples¶

>>> from river import optim

>>> loss = optim.losses.Quantile(0.5)
>>> loss(1, 3)
1.0

0.5

-0.5


Methods¶

call

Returns the loss.

Parameters

• y_true
• y_pred

Returns

The loss(es).

Return the gradient with respect to y_pred.

Parameters

• y_true
• y_pred

Returns

mean_func

Mean function.

This is the inverse of the link function. Typically, a loss function takes as input the raw output of a model. In the case of classification, the raw output would be logits. The mean function can be used to convert the raw output into a value that makes sense to the user, such as a probability.

Parameters

• y_pred

Returns