When read_raw_data_for_training is set to False when invoking the main
function, common.transform_data was being called on raw train and test
data anyway.  This fix moves the transformation to the block where
read_raw_data_for_training is True. The scenario here is the data has
already been preprocessed, and the user wishes to re-use that
preprocessed data.

Since this is tabular data we're dealing with, the code has been
updated to treat it as such.  The net result is simpler shape related
code.  Education-num is treated as dense here instead of sparse as it
was before.  It might be missing values in the data, so it might call
for some sort of imputation to be done.