pyanno4rt.learning_model.losses

Losses module.

The module aims to provide functions to compute different machine learning outcome model losses.

Overview

Function

brier_loss(true_labels, predicted_labels)

Compute the Brier score loss.

log_loss(true_labels, predicted_labels)

Compute the log loss.
Attributes

loss_map

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Functions

pyanno4rt.learning_model.losses.brier_loss(true_labels, predicted_labels)[source]

Compute the Brier score loss.

Parameters:

  • true_labels (ndarray) – Ground truth label values.

  • predicted_labels (ndarray) – Predicted label values.

Returns:

Brier score loss value.

Return type:

float

pyanno4rt.learning_model.losses.log_loss(true_labels, predicted_labels)[source]

Compute the log loss.

Parameters:

  • true_labels (ndarray) – Ground truth label values.

  • predicted_labels (ndarray) – Predicted label values.

Returns:

Log loss value.

Return type:

float

Attributes

pyanno4rt.learning_model.losses.loss_map