Paper on Generalized Bias/Variance Decomposition

[Gareth James]

The following paper is available in postscript format at 
http://stat.stanford.edu/~gareth under my papers section.



Generalizations of the Bias/Variance Decomposition for Prediction      
Error

Gareth James and Trevor Hastie  (Stanford University)

The bias and variance of a real valued random variable, using squared
error loss, are well understood. However because of recent developments  
in classification techniques it has become desirable to extend these
concepts to general random variables and loss functions. The 0-1
(misclassification) loss function with categorical random variables has
been of particular interest. 
We explore the concepts of variance and bias and develop a decomposition
of the prediction error into functions of the systematic and variable
parts of our predictor.
After providing some examples we conclude with a discussion of the
various definitions that have been proposed.