public void trainE(
	IInputArray samples,
	IInputArray means0,
	IInputArray covs0 = null,
	IInputArray weights0 = null,
	IOutputArray loglikelihoods = null,
	IOutputArray labels = null,
	IOutputArray probs = null
)

Public Sub trainE ( 
	samples As IInputArray,
	means0 As IInputArray,
	Optional covs0 As IInputArray = Nothing,
	Optional weights0 As IInputArray = Nothing,
	Optional loglikelihoods As IOutputArray = Nothing,
	Optional labels As IOutputArray = Nothing,
	Optional probs As IOutputArray = Nothing
)

public:
void trainE(
	IInputArray^ samples, 
	IInputArray^ means0, 
	IInputArray^ covs0 = nullptr, 
	IInputArray^ weights0 = nullptr, 
	IOutputArray^ loglikelihoods = nullptr, 
	IOutputArray^ labels = nullptr, 
	IOutputArray^ probs = nullptr
)

member trainE : 
        samples : IInputArray * 
        means0 : IInputArray * 
        ?covs0 : IInputArray * 
        ?weights0 : IInputArray * 
        ?loglikelihoods : IOutputArray * 
        ?labels : IOutputArray * 
        ?probs : IOutputArray 
(* Defaults:
        let _covs0 = defaultArg covs0 null
        let _weights0 = defaultArg weights0 null
        let _loglikelihoods = defaultArg loglikelihoods null
        let _labels = defaultArg labels null
        let _probs = defaultArg probs null
*)
-> unit 

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.

Reference