Rough set class library for machine learning

Features implemented:

• Indiscernibility relations that are the base for classic - and extended rough set relations.
• Decision systems and space partitions.
• Rough set measures for data set characterization:
  • rough membership
  • rough involvement
  • rough agreement
  • rough class quality

Usage: The library was used in

• Tarragó, D.S., Bello, R., Herrera, F.: Data Complexity by means of Rough Set Measures. In: Proceedings of the Cuba-Flanders Workshop on Machine Learning and Knowledge Discovery (CF-WML-KD2010). Editorial Feijoó, Central University Marta Abreu de Las Villas (2010). (text)

Developed with:

• Java 1.8
• NetBeans IDE 8.2

Dependencies:

• Weka 3.7