StatModelCalcError Method

public virtual float CalcError(
	TrainData data,
	bool test,
	OutputArray resp
)

Public Overridable Function CalcError ( 
	data As TrainData,
	test As Boolean,
	resp As OutputArray
) As Single

public:
virtual float CalcError(
	TrainData^ data, 
	bool test, 
	OutputArray^ resp
)

abstract CalcError : 
        data : TrainData * 
        test : bool * 
        resp : OutputArray -> float32 
override CalcError : 
        data : TrainData * 
        test : bool * 
        resp : OutputArray -> float32 

function CalcError(data, test, resp);

Parameters

data

Type: OpenCvSharp.MLTrainData
the training data

test

Type: SystemBoolean
if true, the error is computed over the test subset of the data, otherwise it's computed over the training subset of the data. Please note that if you loaded a completely different dataset to evaluate already trained classifier, you will probably want not to set the test subset at all with TrainData::setTrainTestSplitRatio and specify test=false, so that the error is computed for the whole new set. Yes, this sounds a bit confusing.

resp

Type: OpenCvSharpOutputArray
the optional output responses.

Return Value

Reference