EMTrainM Method

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

Public Overridable Function TrainM ( 
	samples As InputArray,
	probs0 As InputArray,
	Optional logLikelihoods As OutputArray = Nothing,
	Optional labels As OutputArray = Nothing,
	Optional probs As OutputArray = Nothing
) As Boolean

public:
virtual bool TrainM(
	InputArray^ samples, 
	InputArray^ probs0, 
	OutputArray^ logLikelihoods = nullptr, 
	OutputArray^ labels = nullptr, 
	OutputArray^ probs = nullptr
)

abstract TrainM : 
        samples : InputArray * 
        probs0 : InputArray * 
        ?logLikelihoods : OutputArray * 
        ?labels : OutputArray * 
        ?probs : OutputArray 
(* Defaults:
        let _logLikelihoods = defaultArg logLikelihoods null
        let _labels = defaultArg labels null
        let _probs = defaultArg probs null
*)
-> bool 
override TrainM : 
        samples : InputArray * 
        probs0 : InputArray * 
        ?logLikelihoods : OutputArray * 
        ?labels : OutputArray * 
        ?probs : OutputArray 
(* Defaults:
        let _logLikelihoods = defaultArg logLikelihoods null
        let _labels = defaultArg labels null
        let _probs = defaultArg probs null
*)
-> bool 

function TrainM(samples, probs0, logLikelihoods, labels, probs);