opendataval.dataval.LeaveOneOut

class opendataval.dataval.LeaveOneOut(*args, **kwargs)

Leave One Out data valuation implementation.

References

[1]

R. Cook, Detection of Influential Observation in Linear Regression, Technometrics, Vol. 19, No. 1 (Feb., 1977), pp. 15-18 (4 pages).

Parameters

random_stateRandomState, optional

Random initial state, by default None

__init__(random_state: RandomState | None = None, *args, **kwargs)

Methods

__init__([random_state])
evaluate(y, y_hat)	Evaluate performance of the specified metric between label and predictions.
evaluate_data_values()	Compute data values using Leave One Out data valuation.
input_data(x_train, y_train, x_valid, y_valid)	Store and transform input data for Leave-One-Out data valuation.
input_fetcher(fetcher)	Input data from a DataFetcher object.
input_metric(metric)	Input the evaluation metric.
input_model(pred_model)	Input the prediction model.
input_model_metric(pred_model, metric)	Input the prediction model and the evaluation metric.
setup(fetcher[, pred_model, metric])	Inputs model, metric and data into Data Evaluator.
train(fetcher[, pred_model, metric])	Store and transform data, then train model to predict data values.
train_data_values(*args, **kwargs)	Trains model to predict data values.

Attributes

Evaluators
data_values	Cached data values.