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

Eliuvish Cuicizion

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arXiv · 2405.12390

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

Eliuvish Cuicizion

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Abstract

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.

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Eliuvish Cuicizion. 2025-03-18. A Metric-based Principal Curve Approach for Learning One-dimensional Manifold. https://arxiv.org/abs/2405.12390

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