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Application of locally linear embedding based on improved distance in neuron classification

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成果类型:
期刊论文、会议论文
作者:
Wang, Zhen Zhen;Tong, Xiao Jun;Zeng, Shan
作者机构:
[Zeng, Shan; Wang, Zhen Zhen] School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430023, China
[Tong, Xiao Jun] College of Mathematics and Computer Science, Wuhan Textile University, Wuhan 430077, China
语种:
英文
关键词:
Classification;Linear locally embedding algorithm;Neuron;Support vector machine
期刊:
Advanced Materials Research
ISSN:
1022-6680
年:
2014
卷:
926-930
页码:
2996-2999
会议名称:
2014 International Conference on Materials Science and Computational Engineering, ICMSCE 2014
会议时间:
May 20, 2014 - May 21, 2014
会议地点:
Qingdao, China
会议主办单位:
(1) School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430023, China; (2) College of Mathematics and Computer Science, Wuhan Textile University, Wuhan 430077, China
会议赞助商:
Engineering of Qingdao University;et al;Institute for Computational Science and;Laboratory of Qingdao University;New fiber materials and modern textile State Key
出版者:
Trans Tech Publications Ltd
ISBN:
9783038350996
机构署名:
本校为第一机构
院系归属:
数学与计算机学院
摘要:
For locally linear embedding(LLE) algorithm of the shortcoming, an improved distance algorithm LLE is proposed, in locally linear embedding algorithm the distribution of sample component is different and the Euclidean distance can't reflect sample distance actually. In the experiment, a sample of 231 neurons is obtained, and the morphological parameters of neurons are calculated firstly. Second, the improved locally linear embedding algorithm is used to reduce data dimensionality. Finally, support vector machine(SVM) algorithm is used to train and test samples. Experimental results show under ...

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