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.MLAssembly: Emgu.CV.ML (in Emgu.CV.ML.dll) Version: 3.0.0.2161 (3.0.0.2161)
Syntaxpublic 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[Missing <returns> documentation for "M:Emgu.CV.ML.SVM.TrainAuto(Emgu.CV.ML.TrainData,System.Int32)"]
See Also