title: Empirical measure of multiclass generalization performance: the K-winner machine case.
abstract: Combining the K-winner machine (KWM) model with empirical measurements of a classifier's Vapnik-Chervonenkis (VC)-dimension gives two major results. First, analytical derivations refine the theory that characterizes the generalization performances of binary classifiers. Second, a straightforward extension of the theoretical framework yields bounds to the generalization error for multiclass problems.
authors.affiliation: Dept. of Biophys. and Electron. Eng., Genoa Univ.
authors.forename: S
authors.initials: S
authors.lastname: Ridella
authors.forename: R
authors.initials: R
authors.lastname: Zunino