LPRegularizer¶
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class
ampligraph.latent_features.
LPRegularizer
(regularizer_params=None, verbose=False)¶ Performs LP regularization
\[\mathcal{L}(Reg) = \sum_{i=1}^{n} \lambda_i * \mid w_i \mid_p\]where n is the number of model parameters, \(p \in{1,2,3}\) is the p-norm and \(\lambda\) is the regularization weight.
For example, if \(p=1\) the function will perform L1 regularization. L2 regularization is obtained with \(p=2\).
The nuclear 3-norm proposed in the ComplEx-N3 paper [LUO18] can be obtained with
regularizer_params={'p': 3}
.Methods
__init__
([regularizer_params, verbose])Initializes the hyperparameters needed by the algorithm.
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__init__
(regularizer_params=None, verbose=False)¶ Initializes the hyperparameters needed by the algorithm.
- Parameters
regularizer_params (dictionary) –
Consists of key-value pairs. The regularizer will check the keys to get the corresponding params:
’lambda’: (float). Weight of regularization loss for each parameter (default: 1e-5)
’p’: (int): norm (default: 2)
Example:
regularizer_params={'lambda': 1e-5, 'p': 1}
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