crested.tl.metrics.PearsonCorrelation

Contents

crested.tl.metrics.PearsonCorrelation#

class crested.tl.metrics.PearsonCorrelation(name='pearson_correlation', **kwargs)#: Pearson correlation metric.

Attributes table#

`dtype`
`variables`

Methods table#

`add_variable`(shape, initializer[, dtype, ...])
`add_weight`([shape, initializer, dtype, name])
`from_config`(config)
`get_config`()	Return the serializable config of the metric.
`reset_state`()	Reset the state of the metric.
`result`()	Calculate the result of the metric.
`stateless_reset_state`()
`stateless_result`(metric_variables)
`stateless_update_state`(metric_variables, ...)
`update_state`(y_true, y_pred[, sample_weight])	Update the state of the metric.

Attributes#

PearsonCorrelation.dtype#

PearsonCorrelation.variables#

Methods#

PearsonCorrelation.add_variable(shape, initializer, dtype=None, aggregation='sum', name=None)#

PearsonCorrelation.add_weight(shape=(), initializer=None, dtype=None, name=None)#

classmethod PearsonCorrelation.from_config(config)#

PearsonCorrelation.get_config()#: Return the serializable config of the metric.

PearsonCorrelation.reset_state()#: Reset the state of the metric.

PearsonCorrelation.result()#: Calculate the result of the metric.

PearsonCorrelation.stateless_reset_state()#

PearsonCorrelation.stateless_result(metric_variables)#

PearsonCorrelation.stateless_update_state(metric_variables, *args, **kwargs)#

PearsonCorrelation.update_state(y_true, y_pred, sample_weight=None)#: Update the state of the metric.