pyclustering.cluster.ema.ema_initializer Class Reference

Provides servies for preparing initial means and covariances for Expectation-Maximization algorithm. More...

Public Member Functions
def	__init__ (self, sample, amount)
	Constructs EM initializer. More...
def	initialize (self, init_type=ema_init_type.KMEANS_INITIALIZATION)
	Calculates initial parameters for EM algorithm: means and covariances using specified strategy. More...

Detailed Description

Provides servies for preparing initial means and covariances for Expectation-Maximization algorithm.

Initialization strategy is defined by enumerator 'ema_init_type': random initialization and kmeans with kmeans++ initialization. Here an example of initialization using kmeans strategy:

from pyclustering.utils import read_sample
from pyclustering.samples.definitions import FAMOUS_SAMPLES
from pyclustering.cluster.ema import ema_initializer

sample = read_sample(FAMOUS_SAMPLES.SAMPLE_OLD_FAITHFUL)
amount_clusters = 2

initial_means, initial_covariance = ema_initializer(sample, amount_clusters).initialize()
print(initial_means)
print(initial_covariance)

Definition at line 102 of file ema.py.

Constructor & Destructor Documentation

__init__()

def pyclustering.cluster.ema.ema_initializer.__init__	(		self,
			sample,
			amount
	)

Constructs EM initializer.

Parameters

[in]	sample	(list): Data that will be used by the EM algorithm.
[in]	amount	(uint): Amount of clusters that should be allocated by the EM algorithm.

Definition at line 125 of file ema.py.

Member Function Documentation

initialize()

def pyclustering.cluster.ema.ema_initializer.initialize	(		self,
			init_type = ema_init_type.KMEANS_INITIALIZATION
	)

Calculates initial parameters for EM algorithm: means and covariances using specified strategy.

Parameters

[in]

init_type

(ema_init_type): Strategy for initialization.

Returns

(float|list, float|numpy.array) Initial means and variance (covariance matrix in case multi-dimensional data).

Definition at line 137 of file ema.py.

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

• pyclustering/cluster/ema.py