Combining Dissimilarities for Three-Way Data Classification
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| Format: | Artículo científico |
| Langue: | en |
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Instituto Politécnico Nacional
2011
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| _version_ | 1876463830310060032 |
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| author | Diana Porro Muñoz |
| author_facet | Diana Porro Muñoz |
| contents | Combining Dissimilarities for Three-Way Data Classification Diana Porro Muñoz Isneri Talavera Robert P. W. Duin Mauricio Orozco Alzate Computación three way data Classification combination and dissimilarity representation The representation of objects by multidimensional arrays is widely applied in many research areas. Nevertheless, there is a lack of tools to classify data with this structure. In this paper, an approach for classifying objects represented by matrices is introduced, based on the advantages and success of the combination strategy, and particularly in the dissimilarity representation. A procedure for obtaining the new representation of the data has also been developed, aimed at obtaining a more powerful representation. The proposed approach is evaluated on two threeway data sets. This has been done by comparing the different ways of achieving the new representation, and the traditional vector representation of the objects. 2011 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61520862011 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.15 |
| format | Artículo científico |
| id | redalyc_61520862011 |
| institution | Redalyc |
| language | en |
| publishDate | 2011 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Combining Dissimilarities for Three-Way Data Classification Diana Porro Muñoz Computación three way data Classification combination and dissimilarity representation Combining Dissimilarities for Three-Way Data Classification Diana Porro Muñoz Isneri Talavera Robert P. W. Duin Mauricio Orozco Alzate Computación three way data Classification combination and dissimilarity representation The representation of objects by multidimensional arrays is widely applied in many research areas. Nevertheless, there is a lack of tools to classify data with this structure. In this paper, an approach for classifying objects represented by matrices is introduced, based on the advantages and success of the combination strategy, and particularly in the dissimilarity representation. A procedure for obtaining the new representation of the data has also been developed, aimed at obtaining a more powerful representation. The proposed approach is evaluated on two threeway data sets. This has been done by comparing the different ways of achieving the new representation, and the traditional vector representation of the objects. 2011 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61520862011 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.15 |
| title | Combining Dissimilarities for Three-Way Data Classification |
| topic | Computación three way data Classification combination and dissimilarity representation |
| url | https://www.redalyc.org/articulo.oa?id=61520862011 |