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Titre
Dynamic CUR, an alternative to variable selection in CUR decomposition.
Autor(es)
Sujet
Multivariate analysis
Principal component analysis
CUR decomposition
Correlation
Singular value decomposition
Fecha de publicación
2019
Éditeur
La Habana: Departamento de Matemática Aplicada Facultad de Matemática y Computación Universidad de La Habana
Citación
Barahona, G. V., Barreiro, C. M. M., García, N. G., Gonzalez, S. H., Barba, M. S., & Villardon, M. P. G. (2019). DYNAMIC CUR, AN ALTERNATIVE TO VARIABLE SELECTION IN CUR DECOMPOSITION. Investigación Operacional, 40(3), 391-400.
Resumen
[EN]CUR decomposition is one of the matrix decomposition techniques proposed in the literature for the selection of rows and/or columns of a data matrix. Dynamic CUR is proposed as an alternative to the selection criteria of the CUR decomposition based on probabilistic criteria. This alternative tries to fit the most adequate theoretical probability distribution to the empirical distribution of the leverages obtained from the start and based on it, automatically determines not only the individuals and/or variables that need to be selected, but also their numbers. In this way, Dynamic CUR sets itself apart from CUR in the information selection criteria, dynamizing the calculation of the approximation error starting from an optimal initial selection of parameters based on the most adequate probability distribution. Lastly, with the purpose of facilitating the use of this new method in any practical context, the Dynamic CUR algorithm has been developed in C#.NET and R languages.
URI
ISSN
2224-5405
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