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RSFDGRC
2005
Springer
126views Data Mining» more  RSFDGRC 2005»
14 years 1 months ago
Rough Sets and Higher Order Vagueness
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 se...
Andrzej Skowron, Roman W. Swiniarski
ISMIS
2003
Springer
14 years 26 days ago
Granular Computing Based on Rough Sets, Quotient Space Theory, and Belief Functions
Abstract. A model of granular computing (GrC) is proposed by reformulating, re-interpreting, and combining results from rough sets, quotient space theory, and belief functions. Two...
Y. Y. Yao, Churn-Jung Liau, Ning Zhong
TSDM
2000
151views Data Mining» more  TSDM 2000»
13 years 11 months ago
Rough Sets in Spatio-temporal Data Mining
In this paper I define spatio-temporal regions as pairs consisting of a spatial and a temporal component and I define topological relations between them. Using the notion of rough ...
Thomas Bittner
ISCI
1998
139views more  ISCI 1998»
13 years 7 months ago
A Rough Set Approach to Attribute Generalization in Data Mining
This paper presents a method for updating approximations of a concept incrementally. The results can be used to implement a quasi-incremental algorithm for learning classification...
Chien-Chung Chan
RSFDGRC
2011
Springer
287views Data Mining» more  RSFDGRC 2011»
12 years 10 months ago
Towards Faster Estimation of Statistics and ODEs Under Interval, P-Box, and Fuzzy Uncertainty: From Interval Computations to Rou
Interval computations estimate the uncertainty of the result of data processing in situations in which we only know the upper bounds ∆ on the measurement errors. In interval comp...
Vladik Kreinovich