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Received:February 06, 2012 Revised:March 04, 2012
Received:February 06, 2012 Revised:March 04, 2012
中文摘要: 特征提取在提高分类的准确性中起着非常关键的作用. 对时序特征提取的方法进行归纳分类, 将有利于对特征提取整体性, 全面性的认识. 回顾现有的时间序列中特征提取的方法, 将其总结为四大类, 它们分别是基于基本统计方法的特征提取、基于模型的特征提取、基于变换的特征提取、基于分形维数的特征提取. 针对每一类的特征提取方法, 进一步研究了它相应的分类方法和它在时间序列数据中的应用邻域.
Abstract:The main contributions of this paper are: 1) The main feature extraction approaches are classified into four categories; 2) The main idea of each category is analyzed, the advantages and disadvantages are pointed out; 3) The guidelines of choosing suitable feature extraction approach is suggested.
keywords: time series classification feature extraction
文章编号： 中图分类号： 文献标志码：
基金项目:广东省科技计划项目基金(2011B060500049, 2010B090400545, 2010A040300006)
| Author Name | Affiliation |
| LIN Zhu | Guangdong Computer Center, Guangzhou 510033, China |
| XING Yan | Guangdong University of Technology, Guangzhou 510006, China |
| Author Name | Affiliation |
| LIN Zhu | Guangdong Computer Center, Guangzhou 510033, China |
| XING Yan | Guangdong University of Technology, Guangzhou 510006, China |
引用文本：
林珠,邢延.数据挖掘中适用于分类的时序数据特征提取方法.计算机系统应用,2012,21(10):224-229
LIN Zhu,XING Yan.Survey of Feature Extraction Approaches for Time Series Classification.COMPUTER SYSTEMS APPLICATIONS,2012,21(10):224-229
林珠,邢延.数据挖掘中适用于分类的时序数据特征提取方法.计算机系统应用,2012,21(10):224-229
LIN Zhu,XING Yan.Survey of Feature Extraction Approaches for Time Series Classification.COMPUTER SYSTEMS APPLICATIONS,2012,21(10):224-229
