Measure

kohavi_wolpert_variance

Variance component of the bias-variance decomposition as defined by Kohavi and Wolpert in: R. Kohavi and D. Wolpert (1996), Bias plus variance decomposition for zero-one loss functions, in Proc. of the Thirteenth International Machine Learning Conference (ICML96) This quantity measures how much the learning algorithms guess "bounces around" for the different training sets of the given size. Estimated using the classifier using the sub-sampled cross-validation procedure as specified in: Geoffrey I. Webb & Paul Conilione (2002), Estimating bias and variance from data , School of Computer Science and Software Engineering, Monash University, Australia

Properties

Minimum value
Maximum value
Unit
OptimizationLower is better