Losses¶
losses submodule within the ketos.neural_networks module
This module provides loss functions
 Contents:
FScoreLoss class:

class
ketos.neural_networks.dev_utils.losses.
FScoreLoss
(beta=1.0, **kwargs)[source]¶ Bases:
tensorflow.python.keras.losses.Loss
Loss function based on the inverse of FScore.
When instantiated, the resulting loss function expects the predictions in the ‘y_pred’ argument and the true labels in the ‘y_true’ argument.
 Args:
 beta:float
 The relative weight of recall in relation to precision.
 Examples:
If beta = 1.0, recall has same weight as precision If beta = 0.5, recall has half the weight of precision If beta = 2.0, recall has twice the weight of precision

call
(y_true, y_pred)[source]¶ Invokes the Loss instance.
 Args:
 y_true: Ground truth values. shape = [batch_size, d0, .. dN], except
sparse loss functions such as sparse categorical crossentropy where shape = [batch_size, d0, .. dN1]
y_pred: The predicted values. shape = [batch_size, d0, .. dN]
 Returns:
Loss values with the shape [batch_size, d0, .. dN1].