ExSTraCS: Rule based machine learning, classification and knowledge discovery for complex problems
- Ryan J. Urbanowicz (2014)
- SIGEVOlution Newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation
BibTeX@article{urbanowicz2015rule,
title={Rule-based machine learning classification and knowledge discovery for complex problems},
author={Urbanowicz, Ryan J},
journal={ACM SIGEVOlution},
volume={7},
number={2-3},
pages={3–11},
year={2015},
publisher={ACM}
}
Abstract: Learning classifier systems (LCSs) are an advantageous, powerful, and flexible class of algorithms that have, to date, been underutilized largely due to the perception that they are difficult to apply, evaluate, and interpret. ExSTraCS is an Extended Supervised Tracking and Classifying System based on the Michigan-Style LCS architecture [4]. It offers an accessible, user friendly LCS platform for supervised rule-based machine learning, classification, data mining, prediction, and knowledge discovery. ExSTraCS seeks to make no assumptions about the data, and is therefore model free and particularly well suited to complex problems that are multi-factorial, interacting (nonlinear), heterogeneous, noisy, class imbalanced, multi-class, or larger scale. ExSTraCS is written in Python, open source, well documented, and freely available at sourceforge.net.
ExSTraCS 2.0 User’s Guide
- Ryan J. Urbanowicz and Jason H. Moore (2015)
- Included with ExSTraCS software download on sourceforge.net
ExSTraCS 1.0 User’s Guide
- Ryan J. Urbanowicz and Jason H. Moore (2014)
- Included with ExSTraCS software download on sourceforge.net
Special issue on advances in learning classifier systems [Preface]
- Kamran Shafi, Ryan J. Urbanowicz, Muhammad Iqbal (2013)
- Evolutionary Intelligence
Special issue on advances in learning classifier systems [Preface]
- Danielle Loiacono, Albert Orriols-Puig, Ryan J. Urbanowicz (2012)
- Evolutionary Intelligence
GAMETES User’s Guide
- Ryan J. Urbanowicz, Jeff Kiralis, Jonathan Fisher, and Jason H. Moore (2012)
- Included with GAMETES software download on sourceforge.net