WeightedSumFitter.score

WeightedSumFitter.score(X, y, coords=None, **kwargs)

Score the Bayesian \(R^2\) given inputs X and outputs y.

Note that the score is based on a comparison of the observed data y and the model’s expected value of the data, mu.

Caution

The Bayesian \(R^2\) is not the same as the traditional coefficient of determination, https://en.wikipedia.org/wiki/Coefficient_of_determination.

Parameters:

• X (xr.DataArray) – Input features.

• y (xr.DataArray) – Observed targets to score against the posterior predictive mean.

• coords (dict[str, Any] | None) – Coordinate names for named dimensions. Forwarded to predict(); ignored by the base implementation.

• **kwargs – Reserved for subclass extensions.

Return type:

Series