pyclustering.cluster.ema Namespace Reference

Cluster analysis algorithm: Expectation-Maximization Algorithm for Gaussian Mixture Model. More...

Classes
class	ema
	Expectation-Maximization clustering algorithm for Gaussian Mixture Model (GMM). More...
class	ema_init_type
	Enumeration of initialization types for Expectation-Maximization algorithm. More...
class	ema_initializer
	Provides services for preparing initial means and covariances for Expectation-Maximization algorithm. More...
class	ema_observer
	Observer of EM algorithm for collecting algorithm state on each step. More...
class	ema_visualizer
	Visualizer of EM algorithm's results. More...

Functions
def	gaussian (data, mean, covariance)
	Calculates gaussian for dataset using specified mean (mathematical expectation) and variance or covariance in case multi-dimensional data. More...

Detailed Description

Cluster analysis algorithm: Expectation-Maximization Algorithm for Gaussian Mixture Model.

Implementation based on paper [16].

Authors

Andrei Novikov (pyclu.nosp@m.ster.nosp@m.ing@y.nosp@m.ande.nosp@m.x.ru)

Date

2014-2020

Copyright

GNU Public License

Function Documentation

gaussian()

def pyclustering.cluster.ema.gaussian	(		data,
			mean,
			covariance
	)

Calculates gaussian for dataset using specified mean (mathematical expectation) and variance or covariance in case multi-dimensional data.

Parameters

[in]	data	(list): Data that is used for gaussian calculation.
[in]	mean	(float|numpy.array): Mathematical expectation used for calculation.
[in]	covariance	(float|numpy.array): Variance or covariance matrix for calculation.

Returns

(list) Value of gaussian function for each point in dataset.

Definition at line 48 of file ema.py.

Referenced by pyclustering.cluster.ema.ema.get_probabilities().