Rough sets and higher order vagueness

A Skowron, R Swiniarski - Rough Sets, Fuzzy Sets, Data Mining, and …, 2005 - Springer
A Skowron, R Swiniarski
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 10th …, 2005Springer
We present a rough set approach to vague concept approximation within the adaptive
learning framework. In particular, the role of extensions of approximation spaces in
searching for concept approximation is emphasized. Boundary regions of approximated
concepts within the adaptive learning framework are satisfying the higher order vagueness
condition, ie, the boundary regions of vague concepts are not crisp. There are important
consequences of the presented framework for research on adaptive approximation of vague …
Abstract
We present a rough set approach to vague concept approximation within the adaptive learning framework. In particular, the role of extensions of approximation spaces in searching for concept approximation is emphasized. Boundary regions of approximated concepts within the adaptive learning framework are satisfying the higher order vagueness condition, i.e., the boundary regions of vague concepts are not crisp. There are important consequences of the presented framework for research on adaptive approximation of vague concepts and reasoning about approximated concepts. An illustrative example is included showing the application of Boolean reasoning in adaptive learning.
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