NLLLoss

class ampligraph.latent_features.NLLLoss(eta, loss_params=None, verbose=False)

Negative log-likelihood loss.

As described in [TWR+16].

\[\mathcal{L}(\Theta) = \sum_{t \in \mathcal{G} \cup \mathcal{C}}log(1 + exp(-y \, f_{model}(t;\Theta)))\]

where \(y \in {-1, 1}\) is the label of the statement, \(\mathcal{G}\) is the set of positives, \(\mathcal{C}\) is the set of corruptions, \(f_{model}(t;\Theta)\) is the model-specific scoring function.

Methods

__init__(eta[, loss_params, verbose])

Initialize Loss.

__init__(eta, loss_params=None, verbose=False)

Initialize Loss.

Parameters
  • eta (int) – Number of negatives.

  • loss_params (dict) – Dictionary of hyperparams. No hyperparameters are required for this loss.