tf.keras.losses.tversky | TensorFlow v2.16.1 (original) (raw)
tf.keras.losses.tversky
Stay organized with collections Save and categorize content based on your preferences.
Computes the Tversky loss value between y_true and y_pred.
tf.keras.losses.tversky(
y_true, y_pred, alpha=0.5, beta=0.5
)
This loss function is weighted by the alpha and beta coefficients that penalize false positives and false negatives.
With alpha=0.5 and beta=0.5, the loss value becomes equivalent to Dice Loss.
| Args | |
|---|---|
| y_true | tensor of true targets. |
| y_pred | tensor of predicted targets. |
| alpha | coefficient controlling incidence of false positives. |
| beta | coefficient controlling incidence of false negatives. |
| Returns |
|---|
| Tversky loss value. |
Reference:
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2024-06-07 UTC.