Set cv_score to -np.inf if OLS fit fails

[1313e]

Description

This PR will automatically set the cross-validation score of an ordinary least-squares fit to -np.inf whenever the fit fails during sequential feature selection.
This ensures that whenever a least-squares fit fails, it does not fail the entire regression process, but simply goes to the next one (after all, if a fit fails, it simply means that that fit is terrible and should never be used, not that no fit ever will work).

Also, I made the modification in master, simply because it is a one-liner and I will be deleting the fork anyways afterward.
I can add the change to the CHANGELOG is required of course.

Pull Request Checklist

• Added a note about the modification or contribution to the ./docs/sources/CHANGELOG.md file (if applicable)
• Added appropriate unit test functions in the ./mlxtend/*/tests directories (if applicable)
• Modify documentation in the corresponding Jupyter Notebook under mlxtend/docs/sources/ (if applicable)
• Ran PYTHONPATH='.' pytest ./mlxtend -sv and make sure that all unit tests pass (for small modifications, it might be sufficient to only run the specific test file, e.g., PYTHONPATH='.' pytest ./mlxtend/classifier/tests/test_stacking_cv_classifier.py -sv)
• Checked for style issues by running flake8 ./mlxtend

[coveralls]

Coverage decreased (-0.01%) to 92.349% when pulling 9a6136f on 1313e:master into aa47008 on rasbt:master.