MPSEAS holds for Model-based Per Set Efficient Algorithm Selection and is a follow-up on the work that can be found in our PSEAS repository
Authors: Marie Anastacio, Théo Matricon, Holger Hoos
Acknowledgement: Nathanaël Fijalkow, Laurent Simon
For details see our ECML/PKDD Workshop on Meta-Knowledge Transfer 2022 paper:
Challenges of Acquiring Compositional Inductive Biases via Meta-Learning:
(TODO: update the following :)
# clone this repository
# create your new env
conda create -n pseas
# activate it
conda activate pseas
# install pip
yes | conda install pip
# install this package and the dependencies
pip install -e .
# you can also install dependencies with the following command where their versions are locked:
pip install -r requirements.txt
# You are good to go :)TODO (waiting for publication)