PIE {PIE} | R Documentation |
PIE: A Partially Interpretable Model with Black-box Refinement
Description
The PIE package implements a novel Partially Interpretable Model (PIE) framework introduced by Wang et al. <arxiv:2105.02410>. This framework jointly train an interpretable model and a black-box model to achieve high predictive performance as well as partial model transparency.
Functions
- predict.PIE()
: Main function for generating predictions with the PIE model on dataset.
- PIE()
: Main function for training the PIE model with dataset.
- data_process()
: Process data into the format that can be used by PIE model.
- sparsity_count()
: Counts the number of features used in group lasso.
- RPE()
: Evaluate the RPE of a PIE model.
- MAE()
: Evaluate the MAE of a PIE model.
For more details, see the documentation for individual functions.
Author(s)
Maintainer: Jingyi Yang jy4057@stern.nyu.edu
Authors:
Tong Wang
Yunyi Li
Boxiang Wang