DOC describe fit_intercept and intercept_ behavior in BayesianRidge
@@ -59,11 +59,13 @@ class BayesianRidge(LinearModel, RegressorMixin):
If True, compute the log marginal likelihood at each iteration of the
optimization. Default is False.
- fit_intercept : boolean, optional
- Whether to calculate the intercept for this model. If set
- to false, no intercept will be used in calculations
+ fit_intercept : boolean, optional, default True
+ Whether to calculate the intercept for this model.
+ The intercept is not treated as a probabilistic parameter
+ and thus has no associated variance. If set
+ to False, no intercept will be used in calculations
(e.g. data is expected to be already centered).
- Default is True.
+
normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
@@ -85,6 +87,10 @@ class BayesianRidge(LinearModel, RegressorMixin):
coef_ : array, shape = (n_features,)
Coefficients of the regression model (mean of distribution).
+ intercept_ : float
+ Independent term in decision function. Set to 0.0 if
+ ``fit_intercept = False``.
+
alpha_ : float
Estimated precision of the noise.
