关键词: 粗糙集, 数据补齐, 模糊加权, 相似性度量

Abstract: Currently, data completion methods based on rough sets mostly compute the similarities between the object that contains missing values and other objects that do not contain missing values, and then use the values of the most similar object to complete the missing values. However, the problem in these methods is that all the condition attributes are considered as equally important, and they ignore the differences between condition attributes. Given this problem, a new notion of fuzzy weighted similarity is introduced, and the similarities between different objects are computed based on the dependencies of decision attribute on condition attributes and the significances of condition attributes. Moreover, the data completion method with rough sets based on the measurement of fuzzy weighted similarity is proposed. The validity of the proposed method is demonstrated by the results of comparative experiments.

Key words: rough sets, data completion, fuzzy weighted, similarity measure