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| 基于OLPP符号表示的时间序列分类算法 | |
| 引用本文： | 武天鸿,翁小清. 基于OLPP符号表示的时间序列分类算法[J]. 计算机应用与软件, 2021, 38(1): 303-312. DOI: 10.3969/j.issn.1000-386x.2021.01.051 |
| 作者姓名： | 武天鸿 翁小清 |
| 作者单位： | 河北经贸大学信息技术学院 河北 石家庄 050061;河北经贸大学信息技术学院 河北 石家庄 050061 |
| 摘 要： | 基于符号表示的时间序列分类方法是时间序列数据挖掘的关键技术.大部分现有方法主要针对单个时间序列样本进行符号表示,没有考虑样本间的近邻关系对符号化分类的影响.对此提出一种基于正交局部保持映射(Orthogonal Locality Preserving Projection,OLPP)的时间序列符号表示方法.使用OLPP... |
| 关 键 词： | 时间序列分类 符号表示 正交局部保持映射 信息增益 |
TIME SERIES CLASSIFICATION BASED ON OLPP SYMBOLIC REPRESENTATION |
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| Wu Tianhong,Weng Xiaoqing. TIME SERIES CLASSIFICATION BASED ON OLPP SYMBOLIC REPRESENTATION[J]. Computer Applications and Software, 2021, 38(1): 303-312. DOI: 10.3969/j.issn.1000-386x.2021.01.051 | |
| Authors: | Wu Tianhong Weng Xiaoqing |
| Affiliation: | (College of Information Technology,Hebei University of Economics and Business,Shijiazhuang 050061,Hebei,China) |
| Abstract: | Time series classification based on symbolic representation is the key technology of time series data mining.Most of the existing methods mainly aim at symbolic representation of single time series samples,and do not consider the influence of neighbor relationship between samples on symbolic representation.This paper proposes time series classification based on OLPP symbolic representation.The OLPP was used to reduce the dimension of the original data set,and then we used the information gain to find the best symbol projection intervals and discretization the reduced-dimensional data into a symbol sequence with multiple coefficient binning(MCB).The classification performance of our algorithm is better than that of the existing methods on 20 time series data sets,and the effective use of the nearest neighbor relationship between samples can significantly improve the classification performance of the algorithm. |
| Keywords: | Time series classification Symbolic representation Orthogonal locality preserving projection(OLPP) Information gain |
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