pyclustering.cluster.ema.ema_init_type Class Reference

Enumeration of initialization types for Expectation-Maximization algorithm. More...

Inheritance diagram for pyclustering.cluster.ema.ema_init_type:

Collaboration diagram for pyclustering.cluster.ema.ema_init_type:

Static Public Attributes
int	RANDOM_INITIALIZATION = 0
	Means are randomly taken from input dataset and variance or covariance is calculated based on spherical data that belongs to the chosen means.
int	KMEANS_INITIALIZATION = 1
	Two step initialization. More...

Detailed Description

Enumeration of initialization types for Expectation-Maximization algorithm.

Definition at line 65 of file ema.py.

Member Data Documentation

KMEANS_INITIALIZATION

int pyclustering.cluster.ema.ema_init_type.KMEANS_INITIALIZATION = 1

static

Two step initialization.

The first is calculation of initial centers using K-Means++ method. The second is K-Means clustering using obtained centers in the first step. Obtained clusters and its centers are used for calculation of variance (covariance in case of multi-dimensional) data.

Definition at line 79 of file ema.py.

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The documentation for this class was generated from the following file:

• pyclustering/cluster/ema.py