DOC ensure all attributes are documented for RBFSampler
@@ -44,6 +44,17 @@ class RBFSampler(TransformerMixin, BaseEstimator):
If None, the random number generator is the RandomState instance used
by `np.random`.
+ Attributes
+ ----------
+ random_offset_: ndarray of shape (n_components,), dtype=float64
+ Random offset used to compute the projection in the `n_components`
+ dimensions of the feature space.
+
+ random_weights_: ndarray of shape (n_features, n_components), dtype=float64
+ Random projection directions drawn from the Fourier transform
+ of the RBF kernel.
+
+
Examples
--------
>>> from sklearn.kernel_approximation import RBFSampler
