Work

Logifold: A Geometrical Foundation of Ensemble Machine Learning

Year: 2024
Type: conference-paper
Abstract: We present a local-to-global and measure-theoretical approach to understanding datasets. The core idea is to formulate a logifold structure and to interpret network models with restricted domains as local charts of datasets. In particular, this provides a mathematical foundation for ensemble machine learning. Our experiments demonstrate that logifolds can be implemented to identify fuzzy domains and improve accuracy compared to taking average of model outputs. Additionally, we provide a theoretical example of a logifold, highlighting the importance of restricting to domains of classifiers in an ensemble.
Authors: Inkee Jung, Siu-Cheong Lau
Institution: Boston University
Language: English
Open Access status: green
OpenAlex ID: W4405709683
FWCI: 0.589
Cites: 16
Cited by: 2
Related to: 10