Titlebook: Rough Sets and Knowledge Technology; 10th International C Davide Ciucci,Guoyin Wang,Wei-Zhi Wu Conference proceedings 2015 Springer Interna

吹氣

Dominance-Based Neighborhood Rough Sets and Its Attribute Reduction-based rough set approach has been used widely in multi-attribute and multi-criteria decision by using the dominating relation. Neighborhood rough set aims to deal with hybrid data types. But the preference relation in the context of neighborhood rough set has not been taken into consideration. In t

MORT

Mining Incomplete Data with Many Lost and Attribute-Concept Valueses. Data mining was accomplished using three kinds of probabilistic approximations: singleton, subset and concept. We compared the best results, using all three kinds of probabilistic approximations, for six data sets with lost values and six data sets with attribute-concept values, where missing at

Jacket

易發(fā)怒

Improving Indiscernibility Matrix Based Approach for Attribute Reductionty matrix. An alternative version based on the indiscernibility matrix has been used for this problem to a lesser extent due to its space and time complexity. This paper improves the indiscernibility matrix based approach for computing all reducts. Only indiscernibility matrix cells as well as subse

可行

Imprecise Rules for Data Privacyrting objects may be easily estimated. If the rules with small support include some sensitive data, this estimation of objects is not very good in the sense of data privacy. Considering this fact, we investigate utilization of imprecise rules for privacy protection in rule induction. Imprecise rules

外科醫(yī)生

MONY

潔凈

Knowledge Spaces and Reduction of Covering Approximation Spacess on the universe form a knowledge space. This paper focuses on the theoretic study of knowledge spaces of covering approximation spaces. One kind of dependence relations among covering approximation spaces is introduced, the relationship between the dependence relation and lower and upper covering

Dungeon

Families of the Granules for Association Rules and Their Properties we consider the new granules defined by an implication, and propose a . in a table with exact data. Each family consists of the four granules, and we show that three criterion values, ., ., and ., can easily be obtained by using the four granules. Then, we extend this framework to tables with non-d

FLACK

Rough Sets and Three-Way Decisions respect to acting, we design most effective strategies for processing the three regions. The identification and explicit investigation of different strategies for different regions are a distinguishing feature of three-way decisions.