After deploying a classifier in production it is essential to support its lifecycle. This paper describes the application of an ensemble of classifiers to support two stages of the...
We study how the error of an ensemble regression estimator can be decomposed into two components: one accounting for the individual errors and the other accounting for the correlat...
We have previously introduced the Learn++ algorithm that provides surprisingly promising performance for incremental learning as well as data fusion applications. In this contribut...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
We present a method which uses example pairs of equal or unequal class labels to select a subspace with near optimal metric properties in a kernel-induced Hilbert space. A represen...
In this paper we propose a very simple FIR pre-filter based method for near optimal least-squares linear approximation of discrete time signals. A digital pre-processing filter,...
Marco Dalai, Riccardo Leonardi, Pierangelo Miglior...