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 servies 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 [12].

Authors
Andrei Novikov (pyclu.nosp@m.ster.nosp@m.ing@y.nosp@m.ande.nosp@m.x.ru)
Date
2014-2018

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().