DACOpt

DACOpt: An Efficient Contesting Procedure for AutoML Optimization


Keywords
AutoML, optimization, Divide, and, conquer, Bayesian
License
xpp
Install
pip install DACOpt==0.1.1

Documentation

DACOpt: An Efficient Contesting Procedure for AutoML Optimization

Contact us

Duc Anh Nguyen

Email:d-dot-a-dot-nguyen-at-liacs-dot-leidenuniv-dot-nl

Website: ecole-itn.eu

Installation

Requirements

As requirements mentioned in requirements.txt, hyperopt and BO4ML as build dependencies:

pip install hyperopt
pip install BO4ML

Installation

You could either install the stable version on pypi:

pip install DACOpt

Or, take the lastest version from github:

pip install git+https://github.com/ECOLE-ITN/DACOpt.git

--

git clone https://github.com/ECOLE-ITN/DACOpt.git
cd DACOpt && python setup.py install --user

Example

See our experiments folder

Citation

Paper Reference

Duc Anh Nguyen, Anna V. Kononova, Stefan Menzel, Bernhard Sendhoff and Thomas Bäck. An Efficient Contesting Procedure for AutoML Optimization. TBA

Acknowledgment

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 766186 (ECOLE).