http://www.emgu.com

The SVM type exposes the following members.

Constructors

  NameDescription
Public methodSVM
Create a support Vector Machine

Methods

  NameDescription
Public methodClear
Clear the statistic model
(Inherited from StatModel.)
Public methodDispose
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.)
Protected methodDisposeObject
Release all the memory associated with the SVM
(Overrides DisposableObject..::..DisposeObject()()()().)
Public methodEquals
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Protected methodFinalize
Destructor
(Inherited from DisposableObject.)
Public methodStatic memberGetDefaultGrid
Get the default parameter grid for the specific SVM type
Public methodGetHashCode
Serves as a hash function for a particular type.
(Inherited from Object.)
Public methodGetSupportVector
The method retrieves a given support vector
Public methodGetSupportVectorCount
The method retrieves the number of support vectors
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodGetVarCount
The method retrieves the number of vars
Public methodLoad
Load the statistic model from file
(Inherited from StatModel.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodPredict
Predicts response for the input sample.
Protected methodReleaseManagedResources
Release the managed resources. This function will be called during the disposal of the current object. override ride this function if you need to call the Dispose() function on any managed IDisposable object created by the current object
(Inherited from DisposableObject.)
Public methodSave
Save the statistic model to file
(Inherited from StatModel.)
Public methodToString
Returns a String that represents the current Object.
(Inherited from Object.)
Public methodTrain
Train the SVM model with the specific paramters
Public methodTrainAuto(Matrix<(Of <<'(Single>)>>), Matrix<(Of <<'(Single>)>>), Matrix<(Of <<'(Byte>)>>), Matrix<(Of <<'(Byte>)>>), MCvSVMParams, Int32)
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.
Public methodTrainAuto(Matrix<(Of <<'(Single>)>>), Matrix<(Of <<'(Single>)>>), Matrix<(Of <<'(Byte>)>>), Matrix<(Of <<'(Byte>)>>), MCvSVMParams, Int32, MCvParamGrid, MCvParamGrid, MCvParamGrid, MCvParamGrid, MCvParamGrid, MCvParamGrid)
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.

Fields

  NameDescription
Protected field_ptr
A pointer to the unmanaged object
(Inherited from UnmanagedObject.)

Properties

  NameDescription
Public propertyParameters
Get a copy of the SVM parameters
Public propertyPtr
Pointer to the unmanaged object
(Inherited from UnmanagedObject.)

See Also