Name
Abstract | ||
|---|---|---|
In order to preprocessing the uncertain system, the paper proposed a new approach based on rough set, which includes reducing
redundant attributes, incomplete data recovery and continuous values discretation. The concept of tolerance relationship similar
matrix via using an extension of equivalence relationship of rough set theory was defined, and by using the corresponding
relationship of condition attributes and decision attributes, the missed data was recovered and the redudant attributes were
deleted. Finally, depending on the concept of super-club data, discretization of the continuous attributes was implemented.
The illustration and experimental results indicate that the approach is effective and efficient.
|
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13498-2_86 | ICSI |
Keywords | Field | DocType |
missing data,rough set,rough set theory | Discretization,Data mining,Matrix similarity,Pattern recognition,Computer science,Rough set,Preprocessor,Equivalence (measure theory),Artificial intelligence,Data recovery,Dominance-based rough set approach,Machine learning | Conference |
Volume | ISSN | ISBN |
6146 | 16113349 | 3-642-13497-1 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
7 | ||