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Code for the paper "On the consistency of supervised learning with missing values"
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Notebook move requirements Jul 10, 2019
analysis iter Jul 9, 2019
boxplots iter Mar 21, 2019
consistency iter Mar 21, 2019
.gitignore iter Mar 1, 2019 update readme Jul 10, 2019
requirements.txt relax requirements Jul 10, 2019

On the consistency of supervised learning with missing values

Authors: Julie Josse (CMAP, Inria), Nicolas Prost (CMAP, Inria), Erwan Scornet (CMAP), Gaël Varoquaux (Inria).

Simple example notebook

Update: the directory Notebook contains a tutorial on key results of the paper.


Access the Notebok via Binder at the following URL

Notes Without Binder, install the required Python libraries via

pip install -r requirements.txt

Code for the simulations in the paper

This repository contains the code for the paper:

Julie Josse, Nicolas Prost, Erwan Scornet, Gaël Varoquaux. On the consistency of supervised learning with missing values. 2019. 〈hal-02024202〉

The directory analysis contains the code for figures 1 and 2 (section 5).

boxplots corresponds to figures 3 and 4 (section 6). There are three separate files: one containing the functions, one containing the script for computation, and two for the visualisation (one of each of the two boxplots).

consistency is used for figure 5 (section 6). There are three files as for the boxplot, but in addition, approximate Bayes rates are computed in bayesrates.R with oracle multiple imputation, as detailed in the paper.

The scripts require the following R packages:


To run script_boxplots.R or script_consistency.R with, say, 20 jobs to parallelize the "for" loop and 10 threads per forest/boosting, do

Rscript boxplots/script_boxplots.R 20 10
Rscript consistency/script_consistency.R 20 10

To build the figures, just run the scripts,

Rscript boxplots/visualisation_boxplot1.R
Rscript boxplots/visualisation_boxplot2.R
python consistency/visualisation_consistency.R

All figure outputs go to the directory figures (created when nonexistent).

Nicolas Prost

July 10, 2019

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