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首页> 外文期刊>Fuzzy Systems, IEEE Transactions on >Hierarchical Granular Clustering: An Emergence of Information Granules of Higher Type and Higher Order
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Hierarchical Granular Clustering: An Emergence of Information Granules of Higher Type and Higher Order

机译：分层粒度聚类：更高类型和更高阶的信息粒度的出现

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摘要

In this study, we introduce a concept of hierarchical granular clustering and establish its algorithmic framework. We show that the proposed model naturally gives rise to information granules that are both of higher order and higher type, offering a compelling justification behind their emergence. In a concise way, we can capture the overall architecture of information granules as a hierarchy exhibiting conceptual layers of increasing abstraction: numeric data → information granules → information granules of type-2, order-2 → … information granules of higher type/order. The elevated type of information granules is reflective of the visible hierarchical facet of processing and the inherent diversity of the individual locally revealed structures in data. While the concept and the methodology deliver some general settings, the detailed algorithmic aspects are discussed in detail when using fuzzy clustering realized by means of fuzzy c-means. Furthermore, for illustrative purposes, we mainly focus on interval-valued fuzzy sets and granular interval fuzzy sets arising at the higher level of the hierarchy. Higher type fuzzy sets are formed with the help of the principle of justifiable granularity. The conceptually sound hierarchy is established in a general way, which makes it equally applicable to various formalisms of representation of information granules. Experiments are reported for synthetic and publicly available datasets.
机译：在这项研究中，我们介绍了分层粒度聚类的概念并建立了其算法框架。我们表明，所提出的模型自然会产生更高阶和更高类型的信息颗粒，从而为它们的出现提供了令人信服的理由。简而言之，我们可以将信息颗粒的整体体系结构捕获为一个层次，展现出越来越抽象化的概念层：数值数据→信息颗粒→类型2，顺序2的信息颗粒→…高级类型/顺序的信息颗粒。信息颗粒的提升类型反映了处理过程的可见层次结构以及数据中各个局部显示结构的固有多样性。虽然概念和方法提供了一些常规设置，但在使用通过模糊c均值实现的模糊聚类时，将详细讨论详细的算法方面。此外，出于说明目的，我们主要关注于层次结构较高级别上出现的区间值模糊集和粒度区间模糊集。借助于合理的粒度原理，可以形成更高类型的模糊集。概念上合理的层次结构是通过一般方式建立的，这使其同样适用于信息颗粒表示的各种形式主义。报告了合成和公开可用数据集的实验。

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