PredDiff: Explanations and Interactions from Conditional Expectations

This repository provides all resources to reproduce the paper: PredDiff: Explanations and Interactions from Conditional Expectations

In particular, we provide ready-to-run jupyter notebooks, which apply PredDiff on different datasets

• synthetic regression (synthetic_dataset.ipynb): (Interaction) relevances for a regressor on the synthetic dataset discussed in the paper
• (tabular) MNIST (mnist.ipynb): (Interaction) relevances for a classifier trained on MNIST seen as a tabular dataset
• NHANES (nhanes.ipynb): (Interaction) relevances for a classifier trained on the NHANES (mortality regression) dataset

In an additional notebook (uci_datasets.ipynb), we invite the user to try PredDiff to obtain (interaction) relevances for models trained on the following additional datasets (not discussed in the paper):

• the 10 UCI regression datasets investigated by Gal et al 2015 in https://github.com/yaringal/DropoutUncertaintyExps (using data as provided in this repository)
• the 7 synthetic classification datasets proposed by Sikonja et al 2008
• the UCI Adult (census income) classification dataset as obtained from https://archive.ics.uci.edu/ml/datasets/adult
• the UCI Bike Sharing regression dataset as obtained from https://archive.ics.uci.edu/ml/datasets/bike+sharing+dataset

Requirements

Install dependencies from pred_diff.yml by running conda env create -f pred_diff.yml and activate the environment via conda activate pred_diff