Open ncfrey opened 3 years ago
I'll put some initial thoughts/suggestions here and @jglazar feel free to change anything you like. The overall motivation is to keep the package as simple, usable, and low-maintenance as possible.
requirements.txt
.ActiveLearner
class that takes a surrogate model and data can be the main class. We probably want to stick with single and joint-optimization to start with and add true Pareto frontier exploration later on.yapf
for formatting, numpy or Google docstring conventions, flake8
for linting. We can set up GitHub actions to automate these checks.
Here we can plan out the structure of
multipAL
.We should specify the following:
multipal/multipal.py
. What classes do we need to write? What does each one do?