We use pip
to install things into a python virtual environment. Refer to requirements.txt
for package requirements.
The R code for computing significance thresholds requires installation of the R package mvtnorm
.
We use nestly
+ SCons
to run simulations.
generate_data.py
-- Generate data.
create_modeler.py
-- Creates an adaptive model developer as specified by the --simulation
argument (options are adversary
and online
).
create_mtp_mechanism.py
-- Create the multiple testing procedure for approving modifications.
main.py
-- Given simulated test and training data, the approval mechanism (i.e. the multiple hypothesis testing procedure), and the adaptive model developer, this will simulate the approval procedure.
The simulation_adversary
folder contains the first set of simulations with an "adversarial" model developer who proposes deleterious modifications. The simulation_reuse
folder contains the second set of simulations where the model developer generally proposes beneficial modifications. To run the simulations, run scons <simulation_folder_name>
.