Notebook: Gaussian process regression in 1D

Use Gaussian processes to represent x-y data.

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Version 1.2 - published on 07 May 2017

doi:10.4231/D3GM81Q2H cite this

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Abstract

Perform Gaussian process regression in x-y data. The code makes use of the excellent GPy package.

 

This version is identical to "gptool" except it is implemented as a notebook tool

Cite this work

Researchers should cite this work as follows:

  • Martin Hunt (2017), "Notebook: Gaussian process regression in 1D," https://nanohub.org/resources/gptool2. (DOI: 10.4231/D3GM81Q2H).

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Tags

  1. Jupyter notebooks
  2. NCN Group - Machine Learning