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mcmc's Introduction

mcmc

Some python code to simulate Markov chain Monte Carlo.

  1. Hard-core model (e.g., binary coloring graph)
  2. q-coloring graph with systematic sweep Gibbs sampling + Fisher Yates shuffle O(q)
  3. Basic MC simulation.

Implementation of several clustring evaluation metrics:

Normalized cut + modularity for non-groundtruth dataset. Adjusted Rand Index (ARI), Rand Index (Rand Index), Normalized Mutual Information (NMI) and Purity

mcmc's People

Contributors

nguyenvo09 avatar

Stargazers

Raktim Mukhopadhyay avatar ZhiJian Zhuo avatar  avatar Lei Yu avatar  avatar

Watchers

James Cloos avatar  avatar

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