Rough Sets in Knowledge Discovery 1
Methodology and Applications
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Beschreibung
The ideas and techniques worked out in Rough Set Theory allow for knowledge reduction and to finding near - to - functional dependencies in data. This fact determines the importance of these techniques for the rapidly growing field of knowledge discovery. Volume 1 and 2 will bring together articles covering the present state of the methods developed in this field of research. Among the topics covered we may mention: rough mereology and rough mereological approach to knowledge discovery in distributed systems; discretization and quantization of attributes; morphological aspects of rough set theory; analysis of default rules in the framework of rough set theory.
Provides many very interesting results Marks out future directions of developments of this domain
Autor*in
Lech Polkowski
Themen in »Rough Sets in Knowledge Discovery 1«
Datenanalyse Fuzzy-Logik complexity data analysis data mining data model data modelling database decision tree distributed systems fuzzy logic information system knowledge discovery learning modeling