Method TrainM

Namespace

OpenCvSharp

Assembly

OpenCvSharp.dll

TrainM(InputArray, InputArray, OutputArray, OutputArray, OutputArray)

Estimate the Gaussian mixture parameters from a samples set.

public virtual bool TrainM(InputArray samples, InputArray probs0, OutputArray logLikelihoods = default, OutputArray labels = default, OutputArray probs = default)

Parameters

samples InputArray

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.

probs0 InputArray

the probabilities

logLikelihoods OutputArray

The optional output matrix that contains a likelihood logarithm value for each sample. It has \f$nsamples \times 1\f$ size and CV_64FC1 type.

labels OutputArray

The optional output "class label" for each sample: \f$\texttt{labels}_i=\texttt{arg max}k(p{i,k}), i=1..N\f$ (indices of the most probable mixture component for each sample). It has \f$nsamples \times 1\f$ size and CV_32SC1 type.

probs OutputArray

The optional output matrix that contains posterior probabilities of each Gaussian mixture component given the each sample. It has \f$nsamples \times nclusters\f$ size and CV_64FC1 type.

Returns

bool