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Dependence degree (DD) and importance degree (ID) of patterns are crucial for pattern appraisement and model reconstruction. In rough set data analysis (RSDA), DD and ID lack robustness because the lower approximation set is terribly unstable under the indiscernibility relation perturbation. Statistical inference is a good way to deal with this instability. However, the fixed-value hypothesis testing...
The field of distributed data mining (DDM) has emerged as an active area in recent years because the key challenge in knowledge discovery is the extraction of knowledge from massive databases. Rough set theory (RST) is one of the powerful approaches in data mining, which has been demonstrated to have its usefulness in successfully solving a variety of problems. But there is almost no literature related...
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