The ROC region of a regression tree

Hua Jin and Ying Lu

Statistics & Probability Letters, 2009, vol. 79, issue 7, 936-942

Abstract: Multiple alternative diagnostic tests for one disease are commonly available to clinicians. It is important to use all the good diagnostic predictors simultaneously to establish a new predictor with higher diagnostic accuracy. The linear combinations of multiple predictors are often of particular interest to clinicians. In this paper, we focused on tree-based nonlinear combinations of multiple predictors. A receiver operating characteristic region and its area under the upper boundary were used to evaluate diagnostic utilities for these algorithms. Some mathematical properties were discussed and non-parametric estimation methods were presented.

Date: 2009
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