Skip to main content

Infpy is a python package I have put together that implements some of the algorithms I (John Reid) have used in my research. In particular it has a Gaussian process package that is largely based on the excellent book, Gaussian Processes for Machine Learning by Rasmussen and Williams.

The Gaussian process package is the only infpy package that is extensively documented so far but you are welcome to try out the others. The Gaussian process package has the following attributes:

  • noisy data is easily modelled

  • many different kernels are supported out of the box allowing many models to be tested

  • kernel composition (point-wise sum and product) is intuitive permitting rapid model evaluation

  • maximum likelihood estimation of hyper-parameters facilitates model comparison

  • numpy integration allows easy interoperability with other python scientific toolkits

  • high quality matplotlib plots are easy to create

  • best of both worlds : ease of using an interpreted language but all performance critical linear algebra performed in compiled code

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

infpy-0.4.9.tar.gz (1.6 MB view details)

Uploaded Source

File details

Details for the file infpy-0.4.9.tar.gz.

File metadata

  • Download URL: infpy-0.4.9.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for infpy-0.4.9.tar.gz
Algorithm Hash digest
SHA256 b8452cc51d29b210fcd8cb35c1ba6983c4eb34ac057b4bc661f58058456b5e43
MD5 e19e03f69ed8280f772d6ab9448b9701
BLAKE2b-256 b2817fd37fcdef1ddca5ec16689a12443e062b7cc164090d5ecab3a8d81b4de8

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page