The LNCS journal Transactions on Rough Sets is devoted to the entire
spectrum of rough sets related issues, from logical and mathematical
foundations, through all aspects of rough set theory and its
applications, such as data mining, knowledge discovery, and intelligent
information processing, to relations between rough sets and other
approaches to uncertainty, vagueness, and incompleteness, such as fuzzy
sets and theory of evidence. Volume XV offers a number of research
streams that have grown out of the seminal work by Zdzislaw Pawlak. The
4 contributions included in this volume presents a rough set approach in
machine learning; the introduction of multi-valued near set theory; the
advent of a complete system that supports a rough-near set approach to
digital image analysis; and an exhaustive study of the mathematics of
vagueness.