Mother class for all metrics.
Indicate if a high value is better than a low one or not.
Indicate whether the model takes into consideration the effect of sample weights
Return a fresh estimator with the same parameters.
The clone has the same parameters but has not been updated with any data. This works by looking at the parameters from the class signature. Each parameter is either - recursively cloned if it's a River classes. - deep-copied via
copy.deepcopy if not. If the calling object is stochastic (i.e. it accepts a seed parameter) and has not been seeded, then the clone will not be idempotent. Indeed, this method's purpose if simply to return a new instance with the same input parameters.
Return the current value of the metric.
Revert the metric.
Update the metric.
Indicates whether or not a metric can work with a given model.
- model (river.base.estimator.Estimator)