gluonts.mx.model.canonical package

class gluonts.mx.model.canonical.CanonicalRNNEstimator(freq: str, context_length: int, prediction_length: int, trainer: gluonts.mx.trainer._base.Trainer = gluonts.mx.trainer._base.Trainer(add_default_callbacks=True, callbacks=None, clip_gradient=10.0, ctx=None, epochs=100, hybridize=True, init='xavier', learning_rate=0.001, num_batches_per_epoch=50, weight_decay=1e-08), num_layers: int = 1, num_cells: int = 50, cell_type: str = 'lstm', num_parallel_samples: int = 100, cardinality: List[int] = [1], embedding_dimension: int = 10, distr_output: gluonts.mx.distribution.distribution_output.DistributionOutput = gluonts.mx.distribution.student_t.StudentTOutput())

Bases: gluonts.mx.model.canonical._estimator.CanonicalEstimator

lead_time: int

prediction_length: int