An incremental linear-time learning algorithm for the Optimum-Path Forest classifier
arXiv:1604.03346 · doi:10.1016/j.ipl.2017.05.004
Abstract
We present a classification method with incremental capabilities based on the Optimum-Path Forest classifier (OPF). The OPF considers instances as nodes of a fully-connected training graph, arc weights represent distances between two feature vectors. Our algorithm includes new instances in an OPF in linear-time, while keeping similar accuracies when compared with the original quadratic-time model.
submitted to IPL Journal for consideration in Nov/2016