pyrichlet 0.0.2

A package for density estimation and clustering using infinite gaussian mixtures with stick-breaking weighting structures

Project description

Pyrichlet is a package useful for doing data analysis via density estimation and clustering using gaussian mixtures with weighting structures generated with the stick-breaking method.

Installation

This project is hosted in pip, it's enought to do

pip install pyrichlet

Usage

The weighting structure models that this package implements are

• DirichletDistribution
• DirichletProcess
• PitmanYorProcess
• GeometricProcess
• BetaInBetaProcess
• BetaInDirichletProcess
• BetaBernoulliProcess
• BetaBinomialProcess

They can be imported and initialized as

from pyrichlet import weight_models

wm = weight_models.DirichletProcess()

For each weighting structure there is an associated gaussian mixture model, formerly

• DirichletDistributionMixture
• DirichletProcessMixture
• PitmanYorMixture
• GeometricProcessMixture
• BetaInBetaMixture
• BetaInDirichletProcess
• BetaBernoulliMixture
• BetaBinomialMixture

The mixture models can fit array or dataframe data

from pyrichlet import mixture_models

mm = mixture_models.DirichletProcessMixture()
y = [1, 2, 3, 4]
mm.fit_gibbs(y)

x = 2.5
f_x = mm.gibbs_eap_density(x)