VUSvar: Variance of the volume under the ROC surface

In VUROCS: Volume under the ROC Surface for Multi-Class ROC Analysis

Description

Computes the volume under the ROC surface (VUS) and its variance for a vector of realisations y (i.e. realised categories) and a vector of predictions fx (i.e. values of the a ranking function f) for the purpose of assessing the discrimiatory power in a multi-class classification problem.

Usage

VUSvar(y, fx, ncores = 1, clusterType = "SOCK")

Arguments

y	a vector of realized categories.
fx	a vector of predicted values of the ranking function f.
ncores	number of cores to be used for parallelized computations. The default value is 1.
clusterType	type of cluster to be initialized in case more than one core is used for calculations. The default values is "SOCK". For details regarding the different types to be used, see makeCluster.

Value

The implemented algorithm is based on Waegeman, De Baets and Boullart (2008). A list of length two is returned, containing the following components:

var	variance of the volume under the ROC surface
val	volume under the ROC surface

References

Waegeman W., De Baets B., Boullart L., 2008. On the scalability of ordered multi-class ROC analysis. Computational Statistics & Data Analysis 52, 3371-3388.

Examples

VUSvar(rep(1:5,each=3),c(1,2,3,rep(2:5,each=3)))

VUROCS documentation built on April 14, 2020, 6:47 p.m.