Bias component (squared) of the bias-variance decomposition as defined by Kohavi and Wolpert in: R. Kohavi & 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 closely the learning algorithms average guess over all possible training sets of the given training set size matches the target. 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


Minimum value
Maximum value
OptimizationLower is better