GaussianMixture

class pyspark.mllib.clustering.GaussianMixture[source]

Learning algorithm for Gaussian Mixtures using the expectation-maximization algorithm.

New in version 1.3.0.

Methods

Methods Documentation

classmethod train(rdd, k, convergenceTol=0.001, maxIterations=100, seed=None, initialModel=None)[source]

Train a Gaussian Mixture clustering model.

Parameters
  • rdd – Training points as an RDD of Vector or convertible sequence types.

  • k – Number of independent Gaussians in the mixture model.

  • convergenceTol – Maximum change in log-likelihood at which convergence is considered to have occurred. (default: 1e-3)

  • maxIterations – Maximum number of iterations allowed. (default: 100)

  • seed – Random seed for initial Gaussian distribution. Set as None to generate seed based on system time. (default: None)

  • initialModel – Initial GMM starting point, bypassing the random initialization. (default: None)

New in version 1.3.0.