Abstract
The use of tree-based models will be relatively unfamiliar to statisticians, although researchers in other fields have found trees to be an attractive way to express knowledge and aid decision-making. Keys such as Figure 14.1 are common in botany and in medical decision-making, and provide a way to encapsulate and structure the knowledge of experts to be used by less-experienced users. Notice how this tree uses both categorical variables and splits on continuous variables.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Unfortunately the version supplied in S-PLUS 3.0 to 3.3 contains several errors. Our library treef ix contains a replacement function.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer Science+Business Media New York
About this chapter
Cite this chapter
Venables, W.N., Ripley, B.D. (1997). Tree-based Methods. In: Modern Applied Statistics with S-PLUS. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-2719-7_14
Download citation
DOI: https://doi.org/10.1007/978-1-4757-2719-7_14
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-2721-0
Online ISBN: 978-1-4757-2719-7
eBook Packages: Springer Book Archive