Creating predictive checklists from data using integer programming.

Overview

Learning Optimal Predictive Checklists

A Python package to learn simple predictive checklists from data subject to customizable constraints. For more details please see our NeurIPS 2021 paper.

Contents

Installation

1. Installing the Package

Our package is available on PyPI. Simply run the following with Python >= 3.7:

pip install predictive-checklists

2. Installing a MIP Solver

2.1. CPLEX (Recommended)

CPLEX is a proprietary optimization software package from IBM. All of the experiments in our paper were ran with CPLEX. To install CPLEX, download and install CPLEX Optimization Studio (we use version 20.1.0). If you are affiliated with an academic institution, you can obtain a free academic version.

After installing CPLEX Optimization Studio, install the cplex Python package by following the instructions here. Note that we create our MIP in this project using cplex, not docplex.

2.2. Python-MIP (Not Recommended)

If you are not able to obtain CPLEX, we provide the same formulation using Python-MIP, which allows for the use of CBC, a free and open source MIP solver. You will not have to install any additional packages if you choose to use Python-MIP with CBC.

However, note that all of the experiments in our paper were conducted using CPLEX. In limited tests, Python-MIP with CBC seems to perform markedly worse than CPLEX for the same solution time, and so we provide no guarantees on the performance of Python-MIP.

Usage

We provide the following examples as Jupyter Notebooks:

  1. Getting Started
  2. Creating Fair Checklists

Reproducing the Paper

See reproducing_paper.md.

Citation

If you use this code or package in your research, please cite the following publication:

@article{zhang2021learning,
  title={Learning Optimal Predictive Checklists},
  author={Zhang, Haoran and Morris, Quaid and Ustun, Berk and Ghassemi, Marzyeh},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}
Owner
Healthy ML
Healthy ML
Code for the paper "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks"

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks This is a Python3 / Pytorch implementation of TadGAN paper. The associated

Arun 92 Dec 03, 2022
Implementation of parameterized soft-exponential activation function.

Soft-Exponential-Activation-Function: Implementation of parameterized soft-exponential activation function. In this implementation, the parameters are

Shuvrajeet Das 1 Feb 23, 2022
Active window border replacement for window managers.

xborder Active window border replacement for window managers. Usage git clone https://github.com/deter0/xborder cd xborder chmod +x xborders ./xborder

deter 250 Dec 30, 2022
Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer

Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer Paper on arXiv Public PyTorch implementation of two-stage peer-reg

NNAISENSE 38 Oct 14, 2022
Official pytorch implementation of paper "Inception Convolution with Efficient Dilation Search" (CVPR 2021 Oral).

IC-Conv This repository is an official implementation of the paper Inception Convolution with Efficient Dilation Search. Getting Started Download Imag

Jie Liu 111 Dec 31, 2022
PyTorch implementation of PP-LCNet: A Lightweight CPU Convolutional Neural Network

PyTorch implementation of PP-LCNet Reproduction of PP-LCNet architecture as described in PP-LCNet: A Lightweight CPU Convolutional Neural Network by C

Quan Nguyen (Fly) 47 Nov 02, 2022
The official implementation of You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient.

You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient (paper) @misc{zhang2021compress,

46 Dec 07, 2022
Pytorch implementation of "Geometrically Adaptive Dictionary Attack on Face Recognition" (WACV 2022)

Geometrically Adaptive Dictionary Attack on Face Recognition This is the Pytorch code of our paper "Geometrically Adaptive Dictionary Attack on Face R

6 Nov 21, 2022
🚀 PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)"

PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)" Unofficial PyTorch Implementation of Progressi

Vitaliy Hramchenko 58 Dec 19, 2022
Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)

ProbAI 2021 - Probabilistic Programming and Variational Inference Tutorial with Pryo Day 1 (June 14) Slides Notebook: students_PPLs_Intro Notebook: so

PGM-Lab 46 Nov 01, 2022
QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing

QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing Environment Tested on Ubuntu 14.04 64bit and 16.04 64bit Installation # disabl

gts3.org (<a href=[email protected])"> 581 Dec 30, 2022
Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients

LSF-SAC Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy G

Hanhan 2 Aug 14, 2022
Utilities to bridge Canvas-generated course rosters with GitLab's API.

gitlab-canvas-utils A collection of scripts originally written for CSE 13S. Oversees everything from GitLab course group creation, student repository

Eugene Chou 5 Jun 08, 2022
Embracing Single Stride 3D Object Detector with Sparse Transformer

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

TuSimple 385 Dec 28, 2022
Convert Table data to approximate values with GUI

Table_Editor Convert Table data to approximate values with GUIs... usage - Import methods for extension Tables. Imported method supposed to have only

CLJ 1 Jan 10, 2022
code for our ECCV 2020 paper "A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation"

Code for our ECCV (2020) paper A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation. Prerequisites: python == 3.6.8 pytorch ==1.1.0

32 Nov 27, 2022
Image based Human Fall Detection

Here I integrated the YOLOv5 object detection algorithm with my own created dataset which consists of human activity images to achieve low cost, high accuracy, and real-time computing requirements

UTTEJ KUMAR 12 Dec 11, 2022
GitHub repository for "Improving Video Generation for Multi-functional Applications"

Improving Video Generation for Multi-functional Applications GitHub repository for "Improving Video Generation for Multi-functional Applications" Pape

Bernhard Kratzwald 328 Dec 07, 2022
Rethinking Portrait Matting with Privacy Preserving

Rethinking Portrait Matting with Privacy Preserving This is the official repository of the paper Rethinking Portrait Matting with Privacy Preserving.

184 Jan 03, 2023
Music library streaming app written in Flask & VueJS

djtaytay This is a little toy app made to explore Vue, brush up on my Python, and make a remote music collection accessable through a web interface. I

Ryan Tasson 6 May 27, 2022