gram schmidt process for orthonormal basis vectors and checking dimensionality

[rasbt]

Description

Adds two new functions, vectorspace_orthonormalization and vectorspace_dimensionality were added to mlxtend.math to use the Gram-Schmidt process to convert an orthogonal vectorspace into orthonormal basis vectors and to compute the dimensionality of a vectorspace, respectively.

Related issues or pull requests

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 nosetests ./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., nosetests ./mlxtend/classifier/tests/test_stacking_cv_classifier.py -sv)
• Checked for style issues by running flake8 ./mlxtend

[coveralls]

Coverage increased (+0.03%) to 91.205% when pulling 17f1483 on orthonormal into 10a7d6b on master.