Titlebook: Rough Sets and Knowledge Technology; 4th International Co Peng Wen,Yuefeng Li,Guoyin Wang Conference proceedings 2009 Springer-Verlag Berli

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Evolutionary Rough K-Means Clusteringh the rough K-means algorithm has shown that it provides a reasonable set of lower and upper bounds for a given dataset. Evaluation of clustering obtained from rough K-means using various cluster validity measures has also been promising. However, rough K-means algorithm has not been explicitly show

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Development of the Data Preprocessing Agent’s Knowledge for Data Mining Using Rough Set Theorycially involving large dataset. It is crucial for a data miner to be able to determine the appropriate data preprocessing techniques for a particular data set as it will save the processing time and retain the quality of the data for data mining. Current data mining researchers use agent as a tool t

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Improving Rules Quality Generated by Rough Set Theory for the Diagnosis of Students with LDs throughue. In this study, we apply rough set theory (RST), which may produce meaningful explanations or rules, to the LD identification application. We also propose to mix samples collected from sources with different LD diagnosis procedure and criteria. By pre-processing these mixed samples with some simp

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Topological Residuated Lattice: A Unifying Algebra Representation of Some Rough Set Modelszy rough set and intuitionistic fuzzy rough set), a new notion of the topological residuated lattice is introduced, and its basic properties are given. Moreover, the relationship between topological residuated lattice and triangle algebra are investigated.

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A Time-Reduction Strategy to Feature Selection in Rough Set Theoryhave been proposed, however, quite often, these methods are computationally time-consuming. To overcome this shortcoming, we introduce a time-reduction strategy, which can be used to accelerate a heuristic process of feature selection. Based on the proposed strategy, a modified feature selection alg

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Reducts Evaluation Methods Using Lazy Algorithmsand inhibitory decision rules. Calculated values are used later to estimate the quality of the reducts. The two proposed algorithms have polynomial time complexity. The results obtained by both approaches were compared with performance of the two classifiers .-NN and Naive Bayesian Classifier..All a

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Knowledge Reduction in Formal Contexts Based on Covering Rough Setsn this paper, by investigating relationship between covering rough set and concept lattice, we study attribute reduction of formal context. Judgement theorems of consistent attribute sets and reduct attribute sets are given.

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