Naive Bayes: Skip NULL values (not rows) from training

Jira: MADLIB-614, 749

NULL values in attribute values cannot be directly used for training
the model. Currently rows with NULL values are completely ignored.
This becomes a problem in datasets that have many rows with at least
one NULL value. We can currently ignore just the specific attribute
which is NULL instead of ignoring the whole row. This should be
changed to better NULL handling, similar to the feature in R.
Start working on the cross-validation part.
Start programming cross_validation.sql_in
Continue programming cross_validation.sql_in
Cross validation almost done!

Several small things still need to be wrapped up.
Added the step to clean up all temporary tables at the end of cross
validation.
Change Modules.yml to install validation module, also corrected lots of
small bugs in cross_validation.sql_in
Added linear SVM to convex module
Added logistic regression to convex module

not much more than just sed 's|linear_svm|logit|g'
Added conjugate gradient for convex module

linear SVM as an example task
a minor comment fix in regress/linear
Added Newton's method to convex

Logistic Regression as an example task
Added ridge regression using convex framework

JIRA: MADLIB-418
Added LASSO using convex framework

JIRA: MADLIB-418
Fixed the way to avoid unused parameter warnings
Use plpgsql to store cross-query info
Fix doxygen for linear SVM, ridge, LASSO
Fix bugs and complete documents for LASSO and ridge regulation

Fixed bugs: dependent vector length changed in the computation
Completed Docs: detailed explanation of the argument meanings
Improved unit test: added a test for LASSO fitting result
Incorporate Aaron's new commit for Convex module

Commit cf661c by Aaron cleaned Wconversion for convex module. Nothing
important has been modified.
Added the option for normalizing the data to LASSO module

This greately improves the convergence. However, this is done by pure
SQL queries, whose speed might be a problem. It would be better if the
same thing can be done in C++.
Lasso - Variable normalization

Moved the SQL queries into Python file.