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Generation of rough sets reducts and constructs based on inter-class and intra-class information

机译:基于类间和类内信息生成粗集约简和构造

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The reduct, originating from the Classic Rough Set Approach (CRSA), is an inclusion minimal subset of attributes that provides discernibility between objects from different classes in at least the same degree as the set of all attributes. It can be thus referred to as being consistent and minimal, which are the two important characteristics of filter-based feature selection. These two characteristics have been also utilized to define reducts within the Dominance-based Rough Set Approach (DRSA). Further, the classic reduct, here referred to as an inter-class reduct, has evolved into what is known as intra-class reduct and construct in CRSA. The idea is that while inter-class reducts utilize only one part of information generated from all pairs of objects, intra-class reducts utilize the remaining part, while constructs utilize both. The paper delivers a final unification of inter-class reducts, intra-class reducts and constructs across CRSA and DRSA, showing how they can be both defined and computed uniformly, i.e. using basically the same concepts and algorithms. It also presents an exact algorithm, capable of generating all exact reduced subsets, but of considerable complexity, as well as a simple and fast heuristic, designed to generate a single reduced subset. Finally, it illustrates the computation process with examples and some experimental evaluation of CRSA constructs, which show how the use of both the inter-class and the intra-class information can assist the attribute reduction process and help obtaining useful insights into the analyzed data set. (C) 2014 Elsevier B.V. All rights reserved.
机译:源自经典粗糙集方法(CRSA)的归约法是属性的包含极小子集,它以至少与所有属性集相同的程度提供了不同类别的对象之间的区别。因此,可以将其称为一致且最小的,这是基于过滤器的特征选择的两个重要特征。这两个特征也已用于定义基于优势的粗糙集方法(DRSA)中的还原。此外,经典还原(这里称为类间还原)已演变为CRSA中的类内还原和构造。这个想法是,尽管类间归约只利用从所有对象对生成的信息的一部分,但类内归约利用余下的部分,而构造则利用这两个部分。本文提供了跨CRSA和DRSA的类间还原,类内还原和构造的最终统一,展示了如何可以统一定义和计算它们,即使用基本相同的概念和算法。它还提出了一种精确的算法,该算法能够生成所有精确的归约子集,但具有相当大的复杂性,以及一种简单,快速的启发式算法,旨在生成单个归约子集。最后,它通过示例和CRSA构造的一些实验评估来说明计算过程,这些过程展示了使用类间和类内信息如何帮助属性缩减过程并帮助获得对分析数据集的有用见解。 (C)2014 Elsevier B.V.保留所有权利。

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