Back Propagation Approach for Semi-supervised Learning in Granular Computing

机译：粒度计算中的半监督学习的反向传播方法

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Zadeh proposes that there are three basic concepts underlying human cognition: granulation, organization and causation and that a granule is a clump of points (objects) drawn together by indistinguishability, similarity, proximity or functionality. Tolerance relation can describe the concept of Granular systems. In this paper, a novel definition of Granular System(GS), which is described by metric function under the framework of tolerance relation, is presented, concepts are created upon GS, and we introduce semi-supervised learning into the Granular computing for concepts creating. For this purpose, a novel back propagation approach is developed for concepts learning. The experiment shows that the new BP is better than traditional EM algorithm when samples do not come from a random source, which has the density we want to estimate.

机译：Zadeh提出了人类认知的三个基本概念：制粒，组织和因果关系，而颗粒是由不可区分性，相似性，接近性或功能性聚集在一起的一堆点（对象）。公差关系可以描述粒度系统的概念。本文提出了一种新的粒度系统定义（GS），它在公差关系的框架下用度量函数来描述，在GS上创建了概念，并将半监督学习引入了用于概念创建的粒度计算。为此，开发了一种用于概念学习的新颖的反向传播方法。实验表明，当样本不是来自随机源时，新的BP算法要优于传统的EM算法。

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来源
《Rough sets and knowledge technology》|2010年|p.468-474|共7页
会议地点 Beijing(CN);Beijing(CN)
作者
Hong Hu; Weimin Liu; Zhongzhi Shi;
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作者单位

The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China;

The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China,Graduate University of Chinese Academy of Sciences, Beijing, 100190, China;

The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类程序设计、软件工程;
关键词
granular computing; semi-supervised learning; back propagation learning;

机译：粒度计算；半监督学习；反向传播学习;

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Back Propagation Approach for Semi-supervised Learning in Granular Computing

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