Prediction Models That Learn to Avoid Missing Values

Prediction Models That Learn to Avoid Missing Values

6 May 2025

Fredrik D. Johansson

ArXiv (abs)PDF HTML

Papers citing "Prediction Models That Learn to Avoid Missing Values"

18 / 18 papers shown

Title
Why do Random Forests Work? Understanding Tree Ensembles as Self-Regularizing Adaptive Smoothers Alicia Curth Alan Jeffares M. Schaar UQCV 67 13 0 02 Feb 2024
Benchmarking Distribution Shift in Tabular Data with TableShift Josh Gardner Zoran Popovic Ludwig Schmidt OOD 51 41 0 10 Dec 2023
MINTY: Rule-based Models that Minimize the Need for Imputing Features with Missing Values Lena Stempfle Fredrik D. Johansson 75 2 0 23 Nov 2023
The Missing Indicator Method: From Low to High Dimensions Mike Van Ness Tomas M. Bosschieter Roberto Halpin-Gregorio Madeleine Udell AI4TS 55 16 0 16 Nov 2022
Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness Vincent Jeanselme Maria De-Arteaga Zhe Zhang Jessica Barrett Brian D. M. Tom FaML 63 13 0 13 Aug 2022
Sharing pattern submodels for prediction with missing values Lena Stempfle Ashkan Panahi Fredrik D. Johansson 47 6 0 22 Jun 2022
Classification of datasets with imputed missing values: does imputation quality matter? Tolou Shadbahr M. Roberts Jan Stanczuk J. Gilbey P. Teare ... T. Mirtti A. Rannikko J. Aston Jing Tang Carola-Bibiane Schönlieb 54 56 0 16 Jun 2022
Fast Sparse Classification for Generalized Linear and Additive Models Jiachang Liu Chudi Zhong Margo Seltzer Cynthia Rudin 28 15 0 23 Feb 2022
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms Trent Kyono Yao Zhang Alexis Bellot M. Schaar CML 70 63 0 04 Nov 2021
What's a good imputation to predict with missing values? Marine Le Morvan Julie Josse Erwan Scornet Gaël Varoquaux AI4TS 72 66 0 01 Jun 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 210 672 0 20 Mar 2021
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 416 10,591 0 17 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 514 42,449 0 03 Dec 2019
On the Existence of Simpler Machine Learning Models Lesia Semenova Cynthia Rudin Ronald E. Parr 61 86 0 05 Aug 2019
On the consistency of supervised learning with missing values Julie Josse Jacob M. Chen Nicolas Prost Erwan Scornet Gaël Varoquaux 66 116 0 19 Feb 2019
BEST : A decision tree algorithm that handles missing values Cédric Beaulac Jeffrey S. Rosenthal 28 24 0 26 Apr 2018
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 809 38,961 0 09 Mar 2016
Prediction with Missing Data via Bayesian Additive Regression Trees A. Kapelner J. Bleich 92 77 0 03 Jun 2013