  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.
