Advertisement

Optimal Binning

  • Ton J. Cleophas
  • Aeilko H. Zwinderman
Chapter

Abstract

Optimal binning is a method for multi-interval discretization of continuous variables. It is used for classification learning, and is already widely applied in econo-/sociometrics.

Keywords

Classification Learning Overweight Child Minimum Description Length Model Entropy Traditional Procedure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Fayyad U, Irani K (1993) Multi-interval discretization of continuous value attributes for classification learning. In: 13th International joint conference of machine learning, Los AltosGoogle Scholar
  2. 2.
    SPSS Statistical Software (2013) www.spss.com. 5 June 2013
  3. 3.
    Vichare NM, Rodgers P, Pecht MG (2013) Methods for binning and density estimates of load parameters for prognostics and health management. www.prognodics.umd.edu. 5 June 2013
  4. 4.
    Sepulveda MJ, Lu C, Sill S, Young J, Edington D (2010) An observational study of an employer intervention for children’s healthy weight behaviors. Pediatrics 126:e1153–e1160PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media Dordrecht 2013

Authors and Affiliations

  • Ton J. Cleophas
    • 1
  • Aeilko H. Zwinderman
    • 2
  1. 1.Department MedicineAlbert Schweitzer HospitalSliedrechtThe Netherlands
  2. 2.Department Biostatistics and EpidemiologyAcademic Medical CenterAmsterdamThe Netherlands

Personalised recommendations