package gpr

  1. Overview
  2. Docs
GPR - Library and Application for Gaussian Process Regression

Install

Dune Dependency

Authors

Maintainers

Sources

gpr-1.3.1.tbz
sha256=28678f583a08b6470bda5f4ddf907b6492e0b73e3f58aa561af35beff344accb
md5=c1e0ce19e20c8a9718f237e028e56d36

Description

Gaussian process regression is a modern Bayesian approach to machine learning, and GPR implements some of the latest advances in this field.

Published: 11 Aug 2017

README

OCaml-GPR - Efficient Gaussian Process Regression in OCaml

This OCaml-library, which also comes with an elaborate example application, implements some of the newest approximation algorithms (e.g. SPGP) for scalable Gaussian process regression for arbitrary covariance functions. Here is an example graph showing the fit of such a sparse Gaussian process to a nonlinear function:

Please refer to the GPR manual for further details and to the online API documentation as programming reference.

Contact Information and Contributing

Please submit bugs reports, feature requests, contributions and similar to the GitHub issue tracker.

Up-to-date information is available at: https://mmottl.github.io/gpr

Dependencies (6)

  1. jbuilder >= "1.0+beta10"
  2. gsl
  3. lacaml >= "9.3.2" & < "10.0.0"
  4. core >= "v0.9.1" & < "v0.13"
  5. base-threads
  6. ocaml >= "4.04"

Dev Dependencies

None

Used by

None

Conflicts

None

OCaml

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