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A kernel for time series classification: application to atmospheric pollutants
dc.contributor.author | Arias Vicente, Marta |
dc.contributor.author | Troncoso, Alicia |
dc.contributor.author | Riquelme, José C. |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics |
dc.date.accessioned | 2013-05-29T07:54:57Z |
dc.date.available | 2014-01-01T03:16:03Z |
dc.date.created | 2012 |
dc.date.issued | 2012 |
dc.identifier.citation | Arias, M.; Troncoso, A.; Riquelme, J. A kernel for time series classification: application to atmospheric pollutants. A: International Conference on Soft Computing Models in Industrial and Environmental Applications. "Advances in Intelligent Systems and Computing". 2012, p. 417-426. |
dc.identifier.isbn | 978-364232921-0 |
dc.identifier.uri | http://hdl.handle.net/2117/19435 |
dc.description.abstract | In this paper a kernel for time-series data is presented. The main idea of the kernel is that it is designed to recognize as similar time series that may be slightly shifted with one another. Namely, it tries to focus on the shape of the time-series and ignores the fact that the series may not be perfectly aligned. The proposed kernel has been validated on several datasets based on the UCR time-series repository [1]. A comparison with the well-known Dynamic Time Warping (DTW) distance and Euclidean distance shows that the proposed kernel outperforms the Euclidean distance and is competitive with respect to the DTW distance while having a much lower computational cost. |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica |
dc.subject.lcsh | Air -- Pollution |
dc.subject.lcsh | Time-series analysis |
dc.subject.other | Atmospheric pollutants |
dc.subject.other | Computational costs |
dc.subject.other | Data sets |
dc.subject.other | Dynamic time warping |
dc.subject.other | Euclidean distance |
dc.subject.other | Time series classifications |
dc.subject.other | Time-series data |
dc.title | A kernel for time series classification: application to atmospheric pollutants |
dc.type | Conference report |
dc.subject.lemac | Aire -- Contaminació |
dc.subject.lemac | Series temporals -- Anàlisi |
dc.contributor.group | Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge |
dc.identifier.doi | 10.1007/978-3-642-32922-7_43 |
dc.rights.access | Open Access |
local.identifier.drac | 11111249 |
dc.description.version | Postprint (author’s final draft) |
local.citation.author | Arias, M.; Troncoso, A.; Riquelme, J. |
local.citation.contributor | International Conference on Soft Computing Models in Industrial and Environmental Applications |
local.citation.publicationName | Advances in Intelligent Systems and Computing |
local.citation.startingPage | 417 |
local.citation.endingPage | 426 |