Code for "Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability"
These are scripts for reproducing our paper "Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability" (preprint).
Contents
adult.csv
contains a copy of the UCI Adult dataset.gauss/
contains the results of our synthetic experimentreal/
contains the results of our UCI Adult experimentnoncensor/
contains the experiment where demographic fields were not hiddencensor/
contains the experiment where demographic fields were hidden- To reproduce the plots in this work, run
python plots.py
experiment.py
is the wrapper for running both our real and synthetic experiments. Setting the flagEXPERIMENT_TYPE
therein to one of ['real', 'synthetic-rcn', 'synthetic-massart'] and runningpython experiment.py
will populategauss/
andreal/
with the relevant experimental data (these folders have been pre-populated for the user's convenience).