# Log¶

Logarithmic loss.

This loss function expects each provided y_pred to be a logit. In other words if must be the raw output of a linear model or a neural network.

## Parameters¶

• weight_pos – defaults to 1.0

• weight_neg – defaults to 1.0

## 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