A New Kernel to use with Discretized Temporal Series
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| Format: | Artículo científico |
| Langue: | en |
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Instituto Politécnico Nacional
2007
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| _version_ | 1876470988999229440 |
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| author | Juan Antonio Ortega Ramírez |
| author_facet | Juan Antonio Ortega Ramírez |
| contents | A New Kernel to use with Discretized Temporal Series Juan Antonio Ortega Ramírez Francisco Javier Cuberos García Vaquero Luis González Abril Francisco Velasco Morente Computación Kernels Discretization Intervals Distance In this paper a new Kernel, from statistical learning theory is proposed to work with symbols chains (words) obtained from a discretization procedure of a continuous features. Although the exact definition of the discretization is not strictly necessary, there must always exist either, a measure of distance or a similarity between symbols in a certain alphabet (a set of symbols). This kernel is applied on a set of television shares obtained from the seven main television stations in Andalusia (Spain). A comparative study for classification purposes is done, and the associated parameter selection is studied. Finally, it must be mentioned that this kernel has certain implications in the type of considered similarity that will be studied in further researches. The small influence of the λ parameter in identification tasks must also be discussed. 2007 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61511102 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.11 |
| format | Artículo científico |
| id | redalyc_61511102 |
| institution | Redalyc |
| language | en |
| publishDate | 2007 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | A New Kernel to use with Discretized Temporal Series Juan Antonio Ortega Ramírez Computación Kernels Discretization Intervals Distance A New Kernel to use with Discretized Temporal Series Juan Antonio Ortega Ramírez Francisco Javier Cuberos García Vaquero Luis González Abril Francisco Velasco Morente Computación Kernels Discretization Intervals Distance In this paper a new Kernel, from statistical learning theory is proposed to work with symbols chains (words) obtained from a discretization procedure of a continuous features. Although the exact definition of the discretization is not strictly necessary, there must always exist either, a measure of distance or a similarity between symbols in a certain alphabet (a set of symbols). This kernel is applied on a set of television shares obtained from the seven main television stations in Andalusia (Spain). A comparative study for classification purposes is done, and the associated parameter selection is studied. Finally, it must be mentioned that this kernel has certain implications in the type of considered similarity that will be studied in further researches. The small influence of the λ parameter in identification tasks must also be discussed. 2007 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61511102 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.11 |
| title | A New Kernel to use with Discretized Temporal Series |
| topic | Computación Kernels Discretization Intervals Distance |
| url | https://www.redalyc.org/articulo.oa?id=61511102 |