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-0.4.10.tar.gz (1.6 MB view details)

Uploaded Source

File details

Details for the file infpy-0.4.10.tar.gz.

File metadata

  • Download URL: infpy-0.4.10.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for infpy-0.4.10.tar.gz
Algorithm Hash digest
SHA256 a1d41385677ae30041df8e38e618121420f69a49492091ac87ceb42a21d8e7ba
MD5 41c2c089408fa65811b92f57c5b74af5
BLAKE2b-256 d30856dcd9c87bf53b15c9085c852d5c9c5893da2aa21eae3bcef00f1978d32c

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