NLLLoss¶
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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.
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__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.
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