CAVE documentation

CAVE stands for Configuration Assessment, Visualization and Evaluation. Optimizing a target algorithm’s configuration is a tiresome process of exploration. A lot of data is usually collected, but not further looked at. CAVE aims to use data that arises during optimization to generate plots and tables for further insights into the optimization process and the target algorithm’s behaviour.

Contents:

Note

If you used CAVE in one of your research projects, please cite us:

@InProceedings{biedenkapp-lion18a,
author = {A. Biedenkapp and J. Marben and M. Lindauer and F. Hutter},
title = {{CAVE}: Configuration Assessment, Visualization and Evaluation},
booktitle = {Proceedings of the International Conference on Learning and Intelligent Optimization (LION‘18)},
year = {2018},
month = jun
}

CAVE is mainly written in Python 3 and continuously tested with Python 3.5 and 3.6. Its Random Forest is written in C++11.