Attribute Reduction Algorithm of Continuous Domain Decision Table Based on Similar Matrix

L. Renguo
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Abstract

Combining fuzzy set with rough set, attribute reduction algorithm of continuous domain decision table is studied. First, continuous attribute value are transformed into fuzzy value with triangular membership function. and then, similarity degree of two fuzzy objects and similarity class of each fuzzy object are defined, in the meantime, characteristic vector of continuous attribute which is made up of similarity class of each fuzzy object is provided. Next, digital characteristic vector of continuous attribute is presented and similar matrix of continuous attributes is proposed. Finally, a new attribute reduction algorithm is provided. Also, the new algorithm is verified through an illustrative example.
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基于相似矩阵的连续域决策表属性约简算法
将模糊集与粗糙集相结合,研究了连续域决策表的属性约简算法。首先,利用三角隶属函数将连续属性值转化为模糊值;然后定义了两个模糊对象的相似度和每个模糊对象的相似类,同时给出了由每个模糊对象的相似类组成的连续属性特征向量。其次,给出了连续属性的数字特征向量,并提出了连续属性的相似矩阵。最后,给出了一种新的属性约简算法。最后,通过实例验证了该算法的有效性。
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