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

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發(fā)表于 2025-3-25 03:20:32 | 只看該作者
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發(fā)表于 2025-3-25 10:33:19 | 只看該作者
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發(fā)表于 2025-3-25 21:11:25 | 只看該作者
Dominance-Based Neighborhood Rough Sets and Its Attribute Reductionhis paper, a novel rough set model, Dominance-based Neighborhood Rough Sets (DNRS), is proposed which aims to process a decision system with hybrid data types where the partial order between objects is taken into consideration. The properties of DNRS are studied. Attribute reduction under DNRS is investigated.
26#
發(fā)表于 2025-3-26 03:19:18 | 只看該作者
Mining Incomplete Data with Many Lost and Attribute-Concept Valuestribute values were located in the same places. For five pairs of data sets the error rate, evaluated by ten-fold cross validation, was significantly smaller for lost values than for attribute-concept values (5?% significance level). For the remaining pair of data sets both interpretations of missing attribute values do not differ significantly.
27#
發(fā)表于 2025-3-26 07:58:06 | 只看該作者
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發(fā)表于 2025-3-26 09:04:31 | 只看該作者
Conference proceedings 2015rts speak; reducts and rules; three-way decisions; logic and algebra; clustering; rough sets and graphs; and modeling and learning. In addition the volume contains 6 contributions by new fellows of the International Rough Set Society, an invited talk and a tutorial.
29#
發(fā)表于 2025-3-26 14:37:45 | 只看該作者
PICKT: A Solution for Big Data Analysis to incremental learning for the Velocity, C refers to composite rough set model for the Variety, K refers to knowledge discovery for the Value and T refers to three-way decisions for the Veracity of Big Data.
30#
發(fā)表于 2025-3-26 17:04:56 | 只看該作者
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