| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4950806 | Information Processing Letters | 2017 | 6 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Moacir Ponti, Mateus Riva,