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Pythonic Expectation-Maximization (EM) implementation for fitting mixtures of probability densities

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mix'EM

mixem is a pure-python implementation of the Expectation-Maximization (EM) algorithm for fitting mixtures of probability distributions. It works in Python 2 and Python 3 (tested with 2.7 and 3.5.1) and uses few dependencies (only NumPy and SciPy).

Old Faithful example

Features

  • Easy-to-use and fully-documented API
  • Built-in support for several probability distributions
  • Easily define custom probability distributions by implementing their probability density function and weighted log-likelihood

Documentation

Find the mix'EM documentation on ReadTheDocs.

Installation

pip install mixem

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Pythonic Expectation-Maximization (EM) implementation for fitting mixtures of probability densities

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