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Titlebook: Rough Sets and Knowledge Technology; Third International Guoyin Wang,Tianrui Li,Yiyu Yao Conference proceedings 2008 Springer-Verlag Berli

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Linguistic Dynamic Systems for Computing with Words and Granular Computingular computing dynamically and numerically. In the earlier stage of its development, fuzzy sets were used as the logic foundation for its analytical formulation and cell-to-cell mappings were applied in its computational framework. Therefore, many concepts and methods developed in ODE-based conventi
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Rough Set Approach to KDD (Extended Abstract)e guide to analysis of different real life problems using rough set methods as well as the presentation of Rough Set Exploration System (RSES) what can be treated as a preliminary material for the main conference and associated workshops..Rough Set theory was introduced by Zdzisław Pawlak in the ear
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Dominance-Based Rough Set Approach for Decision Analysis - A Tutorial, solutions, acts, actions, cases, candidates) evaluated wiht respect to a plurality of their characteristics considered relevant for the problem at hand, and called attributes. For example, a decision can regard:
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Introduction to 3DM: Domain-Oriented Data-Driven Data Miningher and store incredible volumes of data. It creates unprecedented opportunities for large-scale knowledge discovery from huge database. Data mining (DM) technology has emerged as a means of performing this discovery. There are countless researchers working on designing efficient data mining techniq
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Granular Computing: Past, Present, and Futurepreted in terms of nature-inspired computing, human-centered computing, and machine-oriented computing. In this tutorial, I look at the past and the present, and probe the future, of granular computing based on the triarchic theory/model of granular computing.
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A Comparison of Six Approaches to Discretization—A Rough Set Perspectivey method and every data set 30 experiments of ten-fold cross validation were conducted and then means and sample standard deviations were computed. Our results show that for a specific data set it is essential to choose an appropriate discretization method since performance of discretization methods
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