SVMTrainAuto Method (TrainData, Int32)

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The method trains the SVM model automatically by choosing the optimal parameters C, gamma, p, nu, coef0, degree from CvSVMParams. By the optimality one mean that the cross-validation estimate of the test set error is minimal.

Namespace: Emgu.CV.ML
Assembly: Emgu.CV.World (in Emgu.CV.World.dll) Version: 4.0.1.3373 (4.0.1.3373)

Syntax

C++

Copy

public bool TrainAuto(
	TrainData trainData,
	int kFold = 10
)

Public Function TrainAuto ( 
	trainData As TrainData,
	Optional kFold As Integer = 10
) As Boolean

public:
bool TrainAuto(
	TrainData^ trainData, 
	int kFold = 10
)

member TrainAuto : 
        trainData : TrainData * 
        ?kFold : int 
(* Defaults:
        let _kFold = defaultArg kFold 10
*)
-> bool

Parameters

trainData: Type: Emgu.CV.MLTrainData
The training data.
kFold (Optional): Type: SystemInt32
Cross-validation parameter. The training set is divided into k_fold subsets, one subset being used to train the model, the others forming the test set. So, the SVM algorithm is executed k_fold times

Return Value

Type: Boolean
True if training is successful.

Reference

SVM Class

TrainAuto Overload

Emgu.CV.ML Namespace

SVMAddLanguageSpecificTextSet("LST855E76E_0?cpp=::|nu=.");TrainAuto Method (TrainData, Int32)

Parameters

Return Value

Reference

SVMTrainAuto Method (TrainData, Int32)