Quantitative Input Influence tool

This code was originally developed for Datta-Sen-Zick Oakland'16 but has evolved since. Presently the tool requires python2 in some cases so if something is going wrong, make sure you run it with python2 instead of python3.

• To install required python modules:

  make requirements

• To try on the adult dataset run:

  python2 qii.py adult --show-plot

• To see additional options, run:

  python2 qii.py -h

Optional arguments

• -h, --help Show this help message and exit
• -m {average-unary-individual,unary-individual,discrim,banzhaf,shapley} --measure {...} Quantity of interest
• -s SENSITIVE, --sensitive SENSITIVE Sensitive field
• -t TARGET, --target TARGET Target field
• -e, --erase-sensitive Erase sensitive field from dataset
• -p, --show-plot Output plot as pdf
• -o, --output-pdf Output plot as pdf
• -c {logistic,svm,decision-tree,decision-forest}, --classifier {...} Classifier(s) to use
• --max_depth MAX_DEPTH Max depth for decision trees and forests
• --n_estimators N_ESTIMATORS Number of trees for decision forests
• --seed SEED Random seed, auto seeded if not specified
• -a ACTIVE_ITERATIONS, --active-iterations ACTIVE_ITERATIONS Active Learning Iterations
• -r, --record-counterfactuals Store counterfactual pairs for causal analysis
• -i INDIVIDUAL, --individual INDIVIDUAL Index for Individualized Transparency Report
• --batch_mode BATCH_MODE Run in batch mode
• --batch_mode_samples BATCH_MODE_SAMPLES Number of samples to compute.
• --output_suffix OUTPUT_SUFFIX Output suffix for output in batch mode

Currently supported datasets:

• adult : UCI Income dataset
• iwpc : Warfarin dosage
• nlsy97 : Arrest prediction from the NLSY 97

Currently supported measures:

• discrim : Unary QII on discrimination
• average-unary-individual : Average unary QII
• unary-individual : Unary QII on individual outcome (use -i k) for kth individual
• general-inf : Influence on average classification
• shapley : Shapley QII (use -i k) for kth individual
• banzhaf : Banzhaf QII (use -i k) for kth individual