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EMtrainE Method

http://www.emgu.com
Estimate the Gaussian mixture parameters from a samples set. This variation starts with Expectation step. You need to provide initial means of mixture components. Optionally you can pass initial weights and covariance matrices of mixture components.

Namespace:  Emgu.CV.ML
Assembly:  Emgu.CV.World (in Emgu.CV.World.dll) Version: 4.1.1.3497 (4.1.1.3497)
Syntax
public void trainE(
	IInputArray samples,
	IInputArray means0,
	IInputArray covs0 = null,
	IInputArray weights0 = null,
	IOutputArray loglikelihoods = null,
	IOutputArray labels = null,
	IOutputArray probs = null
)

Parameters

samples
Type: Emgu.CVIInputArray
Samples from which the Gaussian mixture model will be estimated. It should be a one-channel matrix, each row of which is a sample. If the matrix does not have CV_64F type it will be converted to the inner matrix of such type for the further computing.
means0
Type: Emgu.CVIInputArray
Initial means of mixture components. It is a one-channel matrix of nclusters x dims size. If the matrix does not have CV_64F type it will be converted to the inner matrix of such type for the further computing.
covs0 (Optional)
Type: Emgu.CVIInputArray
The vector of initial covariance matrices of mixture components. Each of covariance matrices is a one-channel matrix of dims x dims size. If the matrices do not have CV_64F type they will be converted to the inner matrices of such type for the further computing.
weights0 (Optional)
Type: Emgu.CVIInputArray
Initial weights of mixture components. It should be a one-channel floating-point matrix with 1 x nclusters or nclusters x 1 size.
loglikelihoods (Optional)
Type: Emgu.CVIOutputArray
The optional output matrix that contains a likelihood logarithm value for each sample. It has nsamples x 1 size and CV_64FC1 type.
labels (Optional)
Type: Emgu.CVIOutputArray
The optional output "class label" (indices of the most probable mixture component for each sample). It has nsamples x 1 size and CV_32SC1 type.
probs (Optional)
Type: Emgu.CVIOutputArray
The optional output matrix that contains posterior probabilities of each Gaussian mixture component given the each sample. It has nsamples x nclusters size and CV_64FC1 type.
See Also