| 基于距离的粒计算分类算法 |
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| 引用本文： | 陈旭生,刘宏兵,李为华.基于距离的粒计算分类算法[J].信阳师范学院学报(自然科学版),2015(2):271-274. |
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| 作者姓名： | 陈旭生 刘宏兵 李为华 |
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| 作者单位： | 信阳师范学院计算机与信息技术学院 |
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| 基金项目： | 河南省基础与前沿技术研究计划项目(142300410426);河南省教育厅项目(ITE12155);信阳师范学院青年基金项目(2014-QN-054,2014-QN-056) |
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| 摘 要： | 提出了一种基于距离的粒计算分类算法.首先,将粒表示为具有超菱形、超球和超正方体三种形式;第二,设计两粒之间的合并算子,实现不同粒度之间的转换;第三,选取粒度阈值,控制粒之间的合并过程,并构造基于距离的粒计算分类算法.使用UCI机器学习的基准数据集合验证该算法的性能,实验结果验证了基于距离的粒计算分类算法的可行性.
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| 关 键 词： | 粒计算 距离 粒度 模糊包含关系 |
Granular Computing Classification Algorithms Based on Distance |
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| Chen Xusheng;Liu Hongbing;Li Weihua.Granular Computing Classification Algorithms Based on Distance[J].Journal of Xinyang Teachers College(Natural Science Edition),2015(2):271-274. |
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| Authors: | Chen Xusheng;Liu Hongbing;Li Weihua |
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| Institution: | Chen Xusheng;Liu Hongbing;Li Weihua;College of Computer Science and Information Technology,Xinyang Normal University; |
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| Abstract: | The granular computing classification algorithms based on distance were proposed. Firstly,granules were represented as the forms of hyperdiamond,hypersphere and hypercube. Secondly,the union operators were designed to realize the transformation between two granule spaces with different granularity. Thirdly,the thresholds of granularity were used to control the union processes. Then the granular computing classification algorithms based on distance were designed. The benchmark datasets in UCI Learning Repository were used to verify the performance of the algorithms,the feasibility of the granular computing classification algorithms was verified by the experimental results. |
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| Keywords: | granular computing distance granularity fuzzy inclusion relation |
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