Binary Partitioning for CART (Classification and Regression Tree) Methods

Chapter
Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Abstract

Binary partitioning is used to determine the best fit decision cut-off levels for a dataset with false positive and false negative patients. It serves a purpose similar to that of the receiver operating characteristic (ROC) curve method, but, unlike ROC curves, it is adjusted for the magnitude of the samples, and therefore more precise.

Keywords

Receiver Operating Characteristic Receiver Operating Characteristic Curve Peripheral Vascular Disease Internal Node Curve Method 
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.

Copyright information

© The Author(s) 2012

Authors and Affiliations

  1. 1.SliedrechtThe Netherlands
  2. 2.LeidenThe Netherlands

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