--fs_params

Switch

--fs_params

Description

Enables passing explicit feature-selection parameters via --k_best/--pca_comp, bundled into a {'kbest': ..., 'pca': ...} dict.

Argument and Default Value

No argument. Boolean switch, default: False.

Details

Verified: running with --fs_params --k_best 10 --pca_comp 5 completed a full --nfold_test_regression run without error. The resulting featureSelectionParameters dict is passed through to RegressionPredictor.testControlCombos(), but its concrete effect on the feature-selection pipeline wasn't independently confirmed in the output ({modelFS_desc} still showed None in this run) — it likely only changes behavior when combined with a real --feature_selection pipeline that consumes these values.

Other Switches

Optional Switches:

• --k_best, --pca_comp

• --feature_selection

Example Commands

Using the packaged dla_tutorial dataset (see Differential Language Analysis (DLA) Tutorial):

dlatkInterface.py -d dla_tutorial -t msgs -c user_id -f 'feat$1to3gram$msgs$user_id$0_05' \
--outcome_table blog_outcomes --outcomes age --combo_test_regression --fs_params --k_best 10 --pca_comp 5