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Feature extraction from time series data.
- Source :
-
Journal of Computational Methods in Sciences & Engineering . 2009 Supplement 1, Vol. 9, p99-110. 12p. 6 Charts, 4 Graphs. - Publication Year :
- 2009
-
Abstract
- Many scientific and business domains require the collection and analysis of time series data. Feature extraction is an important component of time series data mining. In this paper, we introduce simple and novel techniques for feature extraction from time series data based on moments and slopes. The proposed techniques are capable of handling vertical and horizontal shifts existing between time sequences. They can also handle global scaling and shrinking of the time sequences. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DATA mining
*RESEARCH
*BIOINFORMATICS
*SCIENCE
*ENGINEERING
Subjects
Details
- Language :
- English
- ISSN :
- 14727978
- Volume :
- 9
- Database :
- Academic Search Index
- Journal :
- Journal of Computational Methods in Sciences & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 43520685
- Full Text :
- https://doi.org/10.3233/JCM-2009-0239