Probabilistic Classification Vector Machine at large scale.
Frank-Michael Schleif, Andrej Gisbrecht, Peter Tiňo · University of Birmingham Research Portal (University of Birmingham) · 2015
Probabilistic kernel classifiers are effective approaches to solve classification problems but only few of them can be applied to indefinite kernels as typically observed in life science problems and are often limited to rather small scale problems. We provide a novel batch formulation of the Probabilistic Classification Vector Machine for large scale metric and non-metric data.