--predict_c2r

Switch

--predict_c2r

Description

Predicts with a trained "classify-to-regression" model.

Argument and Default Value

No argument. Boolean switch, default: False.

Details

Same underlying ClassifyToRegressionPredictor as --train_c2r/--test_c2r — see the verified requirement there: it looks up outcomes via a bin_<outcome> column name (e.g. bin_age), not the plain outcome column. Not independently exercised past that point in this pass.

Other Switches

Required Switches:

-d, -g, -t
-f
--outcome_table, --outcomes (with a matching bin_<outcome> column present)
--train_c2r (a trained c2r model)

Example Commands

Using the packaged dla_tutorial dataset (see Differential Language Analysis (DLA) Tutorial), assuming a bin_age column exists in blog_outcomes:

dlatkInterface.py -d dla_tutorial -t msgs -c user_id -f 'feat$1to3gram$msgs$user_id$0_05' \
--outcome_table blog_outcomes --outcomes age --predict_c2r