felipemaiapolo/covariate_shift_high_dimensional

Covariate Shift Adaptation in High-Dimensional and Divergent Distributions

This directory contains the following notebooks and folders:

1. Results Regression (notebook): generates the results for experiments involving regression trees;
2. Results Classification (notebook): generates the results for experiments involving classification trees;
3. Outputs (notebook): generates table and plot from data generated in (1) and (2);
4. Toy Model (notebook): generates plot for toy model;
5. outputs (folder): folder containing the data generated in (1) and (2) - empty;
6. plots(folder): folder containing all the generated plots;
7. Programs (folder): folder containing other code used
   • functions.py: some basic functions;
   • dataset_functions.py: functions that loads datasets and creats covariate shift;
   • w_models.py: models to estimate density ratio;
   • sklearn_models.py: some classes containing sklearn models for our use;
   • select_vars_gmm.py: GMM for feature selection;