dp Package

madbayes Package

Implements some of the MAD-Bayes algorithms by Tamara et al.

dpmeans Module

The DP-means algorithm by Kulis et al.

infpy.madbayes.dpmeans.dpmeans(x, lambda_, progress_plots=False)[source]

The DP-means algorithm by Kulis et al.

Parameters :
  • \(x\) : input data, a sequence of length \(N\)
  • \(\lambda\) : cluster penalty parameter
  • progress_plots : Scatter plot clusters at every iteration
Returns:Cluster indicator variables


  1. Initialise:
  • Number of clusters \(K=1\)
  • Global cluster mean \(\mu_1 = \frac{1}{n} \sum_n x_n\)
  • Cluster indicator variables \(z_n = 0 \quad \forall n\)
  1. Repeat until convergence:
  • For each point \(n\):
    • Compute distance to each cluster \(d_{nk} = ||x_n - \mu_k||^2\)
    • If \(\min d_{nk} > \lambda\) then set \(K=K+1, z_n=K, \mu_k=x_n\)
    • Otherwise set \(z_n= \arg\!\min_k d_{nk}\)
  • For each cluster \(k\), compute \(\mu_k = \frac{1}{|\{n: z_n = k\}|}\sum_{n: z_n = k} x_n\)
infpy.madbayes.dpmeans.plot_clusters(x, z, format_cycler=None)[source]

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