Also with #2406 merged this should be marginal ...

On 03.09.2013, at 23:31, Vlad Niculae <notifications@github.com> wrote:

> In sklearn/decomposition/factor_analysis.py:
> 
> > @@ -86,9 +87,9 @@ class FactorAnalysis(BaseEstimator, TransformerMixin):
> >  
> >      See also
> >      --------
> > -    PCA: Principal component analysis, a similar non-probabilistic
> > -        model model that can be computed in closed form.
> > -    ProbabilisticPCA: probabilistic PCA.
> > +    PCA: Principal component analysis that also implements a probabilistic
> > +        model via a score method. PCA is faster as it can be computed
> > +        in closed form.
> This makes it sound like PCA is always better, I'd avoid such phrasing in docs.
> 
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