Skip to main content

Cluster Analysis

  • Chapter
  • 1495 Accesses

Part of the book series: UNITEXT ((UNITEXTMAT))

Riassunto

Questo capitolo illustra, l’applicazione degli algoritmi di clustering. I record attraverso diversi algoritmi vengono raggruppati in base a delle analogie o a delle omogeneità. Nel clustering non esistono classi predefinite né tanto meno esempi di appartenenza ad una certa classe. Sta a chi applica l’algoritmo stabilire l’eventuale significato da attribuire ai gruppi che si sono formati.

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

Buying options

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
Softcover Book
USD   39.95
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Italia, Milano

About this chapter

Cite this chapter

Dulli, S., Furini, S., Peron, E. (2009). Cluster Analysis. In: Data mining. UNITEXT(). Springer, Milano. https://doi.org/10.1007/978-88-470-1163-2_4

Download citation

  • DOI: https://doi.org/10.1007/978-88-470-1163-2_4

  • Publisher Name: Springer, Milano

  • Print ISBN: 978-88-470-1162-5

  • Online ISBN: 978-88-470-1163-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics