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A Survey of Machine Learning Methods for Big Data

  • Zoila Ruiz
  • Jaime Salvador
  • Jose Garcia-RodriguezEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10338)

Abstract

Nowadays there are studies in different fields aimed to extract relevant information on trends, challenges and opportunities; all these studies have something in common: they work with large volumes of data. This work analyzes different studies carried out on the use of Machine Learning (ML) for processing large volumes of data (Big Data). Most of these datasets, are complex and come from various sources with structured or unstructured data. For this reason, it is necessary to find mechanisms that allow classification and, in a certain way, organize them to facilitate to the users the extraction of the required information. The processing of these data requires the use of classification techniques that will also be reviewed.

Keywords

Big Data Machine learning Classification Clustering 

Notes

Acknowledgements

This work has been funded by the Spanish Government TIN2016-76515-R grant for the COMBAHO project, supported with Feder funds.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Zoila Ruiz
    • 1
  • Jaime Salvador
    • 1
  • Jose Garcia-Rodriguez
    • 2
    Email author
  1. 1.Universidad Central Del Ecuador, Ciudadela UniversitariaQuitoEcuador
  2. 2.Universidad de AlicanteAlicanteSpain

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