Paper ID: 2405.12390

A Metric-based Principal Curve Approach for Learning One-dimensional Manifold

Elvis Han Cui, Sisi Shao

Principal curve is a well-known statistical method oriented in manifold learning using concepts from differential geometry. In this paper, we propose a novel metric-based principal curve (MPC) method that learns one-dimensional manifold of spatial data. Synthetic datasets Real applications using MNIST dataset show that our method can learn the one-dimensional manifold well in terms of the shape.

Submitted: May 20, 2024