Efficient Performance Estimators for SVMs
Predicting the generalization performance of a learner is one of the central goals of learning theory. The previous chapter approached this question based on an intensional description of the learning task. However, such a model is necessarily coarse, since it operates on a high level of abstraction. Training data can give more details about a learning task than an intensional model with only a few parameters. This chapter explores the problem of predicting the generalization performance of an SVM after training data becomes available.