An incremental linear-time learning algorithm for the Optimum-Path Forest classifier
arXiv:1604.03346v51.08 citations
Originality Incremental advance
AI Analysis
This is an incremental improvement for machine learning practitioners needing faster updates in classification tasks.
The paper tackles the problem of efficiently updating the Optimum-Path Forest classifier with new data, achieving linear-time incremental learning while maintaining similar accuracy compared to the original quadratic-time model.
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.