DOC fixed typos in mean_precision_prior in _bayesian_mixture
@@ -140,14 +140,14 @@ class BayesianGaussianMixture(BaseMixture):
mean_precision_prior : float | None, optional.
The precision prior on the mean distribution (Gaussian).
- Controls the extend to where means can be placed. Larger
- values concentrate the means of each clusters around `mean_prior`.
+ Controls the extent of where means can be placed. Larger
+ values concentrate the cluster means around `mean_prior`.
The value of the parameter must be greater than 0.
- If it is None, it's set to 1.
+ If it is None, it is set to 1.
mean_prior : array-like, shape (n_features,), optional
The prior on the mean distribution (Gaussian).
- If it is None, it's set to the mean of X.
+ If it is None, it is set to the mean of X.
degrees_of_freedom_prior : float | None, optional.
The prior of the number of degrees of freedom on the covariance
@@ -257,11 +257,12 @@ class BayesianGaussianMixture(BaseMixture):
The dirichlet concentration of each component on the weight
distribution (Dirichlet).
- mean_precision_prior : float
+ mean_precision_prior_ : float
The precision prior on the mean distribution (Gaussian).
- Controls the extend to where means can be placed.
- Larger values concentrate the means of each clusters around
- `mean_prior`.
+ Controls the extent of where means can be placed.
+ Larger values concentrate the cluster means around `mean_prior`.
+ If mean_precision_prior is set to None, mean_precision_prior_ is set to
+ 1.
mean_precision_ : array-like, shape (n_components,)
The precision of each components on the mean distribution (Gaussian).
