SklearnModelAdapter#

class causalpy.experiments.model_adapter.SklearnModelAdapter[source]#

Adapter for sklearn RegressorMixin backends.

Parameters:: model (RegressorMixin) – CausalPy-compatible sklearn backend model.

Methods

`SklearnModelAdapter.coefficients`()	Return fitted sklearn coefficients.
`SklearnModelAdapter.fit`(X, y, *[, coords])	Fit the sklearn model.
`SklearnModelAdapter.predict`(X, *[, ...])	Return point predictions as singleton posterior draws.
`SklearnModelAdapter.print_coefficients`(labels)	Print sklearn model coefficients.
`SklearnModelAdapter.require_idata`()	Return fitted `InferenceData` or raise an explicit capability error.
`SklearnModelAdapter.score`(X, y, **kwargs)	Return per-output \(R^2\) scores from the sklearn model.

Attributes

`idata`	Return `None` because sklearn models have no `InferenceData`.
`is_bayesian`	Whether the backend is Bayesian (PyMC or pymc-forecast).
`is_ols`	Whether the backend is OLS/sklearn.
`kind`	Backend identifier.
`model`	The underlying sklearn model.
`supports_idata`	Whether the backend can expose ArviZ `InferenceData`.

__init__(model)[source]#