Emgu CV Library Documentation
SVM Class
NamespacesEmgu.CV.MLSVM

www.emgu.com/wiki
Support Vector Machine
Declaration Syntax
C#Visual BasicVisual C++
public class SVM : StatModel
Public Class SVM _
	Inherits StatModel
public ref class SVM : public StatModel
Members
All MembersConstructorsMethodsPropertiesFields



IconMemberDescription
SVM()()()
Create a support Vector Machine

_ptr
A pointer to the unmanaged object
(Inherited from UnmanagedObject.)
Clear()()()
Clear the statistic model
(Inherited from StatModel.)
Dispose()()()
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.)
Dispose(Boolean)
Release the all the memory associate with this object
(Inherited from DisposableObject.)
DisposeObject()()()
Release all the memory associated with the SVM
(Overrides DisposableObject.DisposeObject()()().)
Equals(Object)
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Finalize()()()
Destructor
(Inherited from DisposableObject.)
GetDefaultGrid(SVM_PARAM_TYPE)
Get the default parameter grid for the specific SVM type

GetHashCode()()()
Serves as a hash function for a particular type.
(Inherited from Object.)
GetSupportVector(Int32)
The method retrieves a given support vector

GetSupportVectorCount()()()
The method retrieves the number of support vectors

GetType()()()
Gets the Type of the current instance.
(Inherited from Object.)
GetVarCount()()()
The method retrieves the number of vars

Load(String)
Load the statistic model from file
(Inherited from StatModel.)
MemberwiseClone()()()
Creates a shallow copy of the current Object.
(Inherited from Object.)
Predict(Matrix<(Of <(Single>)>))
Predicts response for the input sample.

Ptr
Pointer to the unmanaged object
(Inherited from UnmanagedObject.)
Save(String)
Save the statistic model to file
(Inherited from StatModel.)
ToString()()()
Returns a String that represents the current Object.
(Inherited from Object.)
Train(Matrix<(Of <(Single>)>), Matrix<(Of <(Single>)>), Matrix<(Of <(Int32>)>), Matrix<(Of <(Int32>)>), SVMParams)
Train the SVM model with the specific paramters

TrainAuto(Matrix<(Of <(Single>)>), Matrix<(Of <(Single>)>), Matrix<(Of <(Int32>)>), Matrix<(Of <(Int32>)>), 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.

TrainAuto(Matrix<(Of <(Single>)>), Matrix<(Of <(Single>)>), Matrix<(Of <(Int32>)>), Matrix<(Of <(Int32>)>), 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.

Inheritance Hierarchy

Assembly: Emgu.CV.ML (Module: Emgu.CV.ML) Version: 1.0.0.0 (1.0.0.0)