Mining Approximative Descriptions of Sets Using Rough Sets

Using concepts from rough set theory we investigate the existence of approximative descriptions of collections of objects that can be extracted from data sets, a problem of interest for biologists that need to find succinct descriptions of families of taxonomic units. Our algorithm is based on an anti-monotonicity of borders of object sets and makes use of an approach that is, in a certain sense, a dual of the Apriori algorithm used in identifying frequent item sets.

• Type: Conference
• Year: 2009
• Where: ISMVL
• Authors: Dan A. Simovici, Selim Mimaroglu
• Keywords: Approximative Descriptions, Artificial Intelligence, Frequent Item Sets, ISMVL 2009, Rough Set Theory