In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction

被引：0
|
作者：
Caroline Wang
Bin Han
Bhrij Patel
Cynthia Rudin
机构：
[1] The University of Texas at Austin,Department of Computer Science
[2] The University of Washington,Department of Information Science
[3] Duke University,Department of Computer Science
[4] Duke University,Department of Statistical Science
来源：
Journal of Quantitative Criminology | 2023年 / 39卷
关键词：
Criminal recidivism; Interpretability; Fairness; COMPAS; Machine learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：519 / 581
页数：62
相关论文
共 50 条
  • [31] Machine Learning Prediction of Human Interpretable Local Features on Echocardiogram
    Ouyang, David
    Ghorbani, Amirata
    Chen, Jonathan H.
    Harrington, Robert A.
    Ashley, Euan A.
    Liang, David
    Zou, James
    CIRCULATION, 2019, 140
  • [32] Interpretable Stroke Risk Prediction Using Machine Learning Algorithms
    Zafeiropoulos, Nikolaos
    Mavrogiorgou, Argyro
    Kleftakis, Spyridon
    Mavrogiorgos, Konstantinos
    Kiourtis, Athanasios
    Kyriazis, Dimosthenis
    INTELLIGENT SUSTAINABLE SYSTEMS, WORLDS4 2022, VOL 2, 2023, 579 : 647 - 656
  • [33] Prediction of the Fatigue Strength of Steel Based on Interpretable Machine Learning
    Liu, Chengcheng
    Wang, Xuandong
    Cai, Weidong
    Yang, Jiahui
    Su, Hang
    MATERIALS, 2023, 16 (23)
  • [34] Interpretable Machine Learning Models for Prediction of UHPC Creep Behavior
    Zhu, Peng
    Cao, Wenshuo
    Zhang, Lianzhen
    Zhou, Yongjun
    Wu, Yuching
    Ma, Zhongguo John
    BUILDINGS, 2024, 14 (07)
  • [35] Interpretable machine learning models for concrete compressive strength prediction
    Hoang, Huong-Giang Thi
    Nguyen, Thuy-Anh
    Ly, Hai-Bang
    INNOVATIVE INFRASTRUCTURE SOLUTIONS, 2025, 10 (01)
  • [36] Interpretable machine learning prediction of all-cause mortality
    Qiu, Wei
    Chen, Hugh
    Dincer, Ayse Berceste
    Lundberg, Scott
    Kaeberlein, Matt
    Lee, Su-In
    COMMUNICATIONS MEDICINE, 2022, 2 (01):
  • [37] Interpretable machine learning prediction of all-cause mortality
    Wei Qiu
    Hugh Chen
    Ayse Berceste Dincer
    Scott Lundberg
    Matt Kaeberlein
    Su-In Lee
    Communications Medicine, 2
  • [38] Interpretable Machine Learning Structure for an Early Prediction of Lane Changes
    Gallitz, Oliver
    De Candido, Oliver
    Botsch, Michael
    Melz, Ron
    Utschick, Wolfgang
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2020, PT I, 2020, 12396 : 337 - 349
  • [39] Prediction of wave runup on beaches using interpretable machine learning
    Kim, Taeyoon
    Lee, Woo-Dong
    OCEAN ENGINEERING, 2024, 297
  • [40] Interpretable Machine Learning
    Chen V.
    Li J.
    Kim J.S.
    Plumb G.
    Talwalkar A.
    Queue, 2021, 19 (06): : 28 - 56
12345