lenskit.sklearn.nmf.NMFConfig#

class lenskit.sklearn.nmf.NMFConfig#

Bases: lenskit.config.common.EmbeddingSizeMixin, pydantic.BaseModel

Configuration for NMFScorer. See the documentation for sklearn.decomposition.non_negative_factorization() for the configuration options.

beta_loss: Literal['frobenius', 'kullback-leibler', 'itakura-saito'] = 'frobenius'#
max_iter: pydantic.PositiveInt#
embedding_size: pydantic.PositiveInt | None#

The dimension of user and item embeddings (number of latent features to learn).

alpha_W: float = 0.0#
alpha_H: float | Literal['same'] = 'same'#
l1_ratio: float = 0.0#