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In rough set theory, the computation of approximation is widely used in the field of knowledge discovery and data mining. As continuous data and noisy data exist extensively in practical applications, it's valuable to computing approximations in continuous data which are accompanied by noises. Three-way decisions model is an important vehicle of processing noises, but it can't directly process continuous data. To resolve this problem, in this paper, neighborhood concept is employed to compute approximations of continuous data. Three-way decisions rules with fundamental notion of tri-partition of a universal set are redefined through the approximations. A general theory of three-way decisions for continuous data with noises is built. The experimental results indicate that the proposed approach is effective and feasible.
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