arXiv Open Access 2018

A Comparative Study of LOWESS and RBF Approximations for Visualization

Michal Smolik Vaclav Skala Ondrej Nedved

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Abstrak

Approximation methods are widely used in many fields and many techniques have been published already. This comparative study presents a comparison of LOWESS (Locally weighted scatterplot smoothing) and RBF (Radial Basis Functions) approximation methods on noisy data as they use different approaches. The RBF approach is generally convenient for high dimensional scattered data sets. The LOWESS method needs finding a subset of nearest points if data are scattered. The experiments proved that LOWESS approximation gives slightly better results than RBF in the case of lower dimension, while in the higher dimensional case

Topik & Kata Kunci

cs.GR

Penulis (3)

Michal Smolik

Vaclav Skala

Ondrej Nedved

Format Sitasi

APA MLA BibTeX

Smolik, M., Skala, V., Nedved, O. (2018). A Comparative Study of LOWESS and RBF Approximations for Visualization. https://arxiv.org/abs/1801.00432

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Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓