SimpleLinearRegression can now process attributes with missing values. Instances with missing values are separated out and the mean class value of those instances is predicted when a new instance has a missing value for that attribute (as in DecisionStump).

git-svn-id: https://svn.cms.waikato.ac.nz/svn/weka@11127 e0a1b77d-ad91-4216-81b1-defd5f83fa92