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

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.

@article{cuicizion2025_2405.12390,
  title={ A Metric-based Principal Curve Approach for Learning One-dimensional Manifold },
  author={ Eliuvish Cuicizion },
  journal={arXiv preprint arXiv:2405.12390},
  year={ 2025 }
}