--num_of_factors

Switch

--num_of_factors N [N2 ...]

Description

Number of factors to select for --factor_adaptation/--res_factor_adaptation. 0 means all factors.

Argument and Default Value

One or more integers. Default: None.

Details

Verified end-to-end (with --factor_selection_type pca): with a single adaptation factor and --num_of_factors 1, the run printed all factors: Index(['is_indUnk'], dtype='object') / nFactors: 1 from: 1 and completed successfully. Multiple values run the whole comparison once per size, similar to --train_bootstraps_ns.

Other Switches

Required Switches:

--factor_adaptation or --res_factor_adaptation

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 --outcome_controls gender is_student \
--combo_test_regression --factor_adaptation --adaptation_factors gender is_student \
--num_of_factors 1 2 --factor_selection_type pca