Skip to main content

Brief Review of Some Optimization Methods

  • Chapter
  • First Online:
Data Analytics
  • 5083 Accesses

Abstract

In this book we have discussed many data analysis methods that use some form of optimization. Many data analysis algorithms are essentially optimization algorithms. In this appendix we briefly review the basics of the optimization methods used in this book: optimization with derivatives, gradient descent, and Lagrange optimization. For a more comprehensive overview of optimization methods the reader is referred to the literature, for example [1, 2, 3].

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 29.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas A. Runkler .

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden

About this chapter

Cite this chapter

Runkler, T. (2012). Brief Review of Some Optimization Methods. In: Data Analytics. Vieweg+Teubner Verlag, Wiesbaden. https://doi.org/10.1007/978-3-8348-2589-6_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-8348-2589-6_10

  • Published:

  • Publisher Name: Vieweg+Teubner Verlag, Wiesbaden

  • Print ISBN: 978-3-8348-2588-9

  • Online ISBN: 978-3-8348-2589-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics