The amount of data being collected across a wide variety of fields today far exceeds our ability to reduce and analyze without the use of automated analysis techniques. Also, the whole data may not be of user interest and may be imperfect. So, it is very challenging to organize these data in a formal system that provides outputs in a more relevant, useful, and structured manner. There are many techniques available to retrieve knowledge from this voluminous amount of data. Rough sets are one among them. The notion of rough sets captures the indiscernibility of elements in a set. But in many real-life situations, an information system establishes the relation between different universes. This led to the extension of a rough set on a single universal set to a rough set on two universal sets. In this chapter, rough sets on two universal sets employing the notion of the lower and upper approximation are discussed. In addition to this, fuzzy rough sets and intuitionistic fuzzy rough sets on two universal sets are also discussed. Finally, a real-life example for the depth classification of the concept is provided. © 2015 by Taylor & Francis Group, LLC.
|Journal||Case Studies in Intelligent Computing: Achievements and Trends|