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Memorias de investigación
Ponencias en congresos:
Massively Parallel Unsupervised Feature Selection on Spark.
Año:2015
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
High dimensional data sets pose important challenges such as the curse of dimensionality and increased computational costs. Dimensionality reduction is therefore a crucial step for most data mining applications. Feature selection techniques allow us to achieve said reduction. However, it is nowadays common to deal with huge data sets, and most existing feature selection algorithms are designed to function in a centralized fashion, which makes them non scalable. Moreover, some of them require the selection process to be validated according to some target, which constrains their applicability to the supervised learning setting. In this paper we propose as novelty a parallel, scalable, exact implementation of an existing centralized, unsupervised feature selection algorithm on Spark, an efficient big data framework for large-scale distributed computation that outperforms MapReduce when applied to multi-pass algorithms. We validate the efficiency of the implementation using 1GB of real Internet traffic captured at a medium-sized ISP.
Internacional
Si
Nombre congreso
19th East-European Conference on Advances in Databases and Information Systems (ADBIS). International Workshop on Big Data Applications and Principles (BigDap)
Tipo de participación
960
Lugar del congreso
Poitiers, France
Revisores
Si
ISBN o ISSN
978-3-319-23201-0
DOI
10.1007/978-3-319-23201-0_21
Fecha inicio congreso
08/09/2015
Fecha fin congreso
11/09/2015
Desde la página
186
Hasta la página
196
Título de las actas
New Trends in Databases and Information Systems. Communications in Computer and Information Science Series, Volume 539. (Funded by FP7 ONTIC project, no. 619633)
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Bruno Ordozgoiti Rubio (UPM)
  • Autor: Sandra Maria Gomez Canaval (UPM)
  • Autor: Bonifacio Alberto Mozo Velasco (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Internet de Nueva Generación
  • Grupo de Investigación: Grupo de Modelización Matemática y Biocomputación
  • Departamento: Sistemas Informáticos
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