Skip to content
Low-level primitives for collapsed Gibbs sampling in python and C++
Python C++ Shell TeX
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.
benchmarks
cmake/Modules
conda
derivations
distributions
doc
examples
include/distributions
src
.gitignore
.travis.yml
CMakeLists.txt
LICENSE.txt
MANIFEST.in
Makefile
README.md
requirements.txt
setup.py
stream.log
test_cmake.sh
update_license.py

README.md

Build Status Code Quality Latest Version

Distributions

Distributions provides low-level primitives for collapsed Gibbs sampling in Python and C++ including:

  • special numerical functions,
  • samplers and density functions from a variety of distributions,
  • conjugate component models (e.g., gamma-Poisson, normal-inverse-chi-squared),
  • clustering models (e.g., CRP, Pitman-Yor), and
  • efficient wrappers for mixture models.

Distributions powered a machine-learning-as-a-service for Prior Knowledge Inc., and now powers machine learning infrastructure at Salesforce.com.

Installation

For python-only support (no C++) you can install with pip:

pip install distributions

For help with other builds, see the installation documentation.

Documentation

The official documentation lives at http://distributions.readthedocs.org/.

Branch-specific documentation lives at

Authors (alphabetically)

License

Copyright (c) 2014 Salesforce.com, Inc. All rights reserved.

Licensed under the Revised BSD License. See LICENSE.txt for details.

Something went wrong with that request. Please try again.