text: Title: Ambiguity in docs about ORPCA and RPCA
  Body: From the docs:
  > Finally, online RPCA includes two alternatives methods
  
  But then the code examples use RPCA, and not ORPCA:
  
  ```python
  > s.decomposition(algorithm="RPCA",
  >                 output_dimension=3,
  >                 method="SGD",
  >                 subspace_learning_rate=1.1)
  ```
  Do the SGD methods apply to RPCA as well? Or are these just being passed into the function and do nothing?
  
  A second question: Does anyone have a good approach for estimating the output_dimension on big data, where the number of components is somewhere between 3 and 20? How should I perform decomposition on such data? Start with output_dimension=20, see how many components are noise, and then reduce by that number?