SVMSvmType Class |
Type of SVM
Inheritance HierarchyNamespace: Emgu.CV.ML
Assembly: Emgu.CV.World.NetStandard (in Emgu.CV.World.NetStandard.dll) Version: 1.0.0
SyntaxThe SVMSvmType type exposes the following members.
Methods| Name | Description | |
|---|---|---|
 | CompareTo | Compares this instance to a specified object and returns an indication of their relative values. (Inherited from Enum.) |
| Equals | Returns a value indicating whether this instance is equal to a specified object. (Inherited from Enum.) |
 | Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) |
| GetHashCode | Returns the hash code for the value of this instance. (Inherited from Enum.) |
| GetType | Gets the Type of the current instance. (Inherited from Object.) |
| GetTypeCode | Returns the type code of the underlying type of this enumeration member. (Inherited from Enum.) |
| HasFlag | Determines whether one or more bit fields are set in the current instance. (Inherited from Enum.) |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
| ToString | Converts the value of this instance to its equivalent string representation. (Inherited from Enum.) |
| ToString(IFormatProvider) | Obsolete. This method overload is obsolete; use ToString. (Inherited from Enum.) |
| ToString(String) | Converts the value of this instance to its equivalent string representation using the specified format. (Inherited from Enum.) |
| ToString(String, IFormatProvider) | Obsolete. This method overload is obsolete; use ToString(String). (Inherited from Enum.) |
Fields| Name | Description | |
|---|---|---|
  | CSvc |
n-class classification (n>=2), allows imperfect separation of classes with penalty multiplier C for outliers
|
| EpsSvr |
Regression. The distance between feature vectors from the training set and the fitting hyper-plane must be less than p. For outliers the penalty multiplier C is used
|
| NuSvc |
n-class classification with possible imperfect separation. Parameter nu (in the range 0..1, the larger the value, the smoother the decision boundary) is used instead of C
|
| NuSvr |
Regression; nu is used instead of p.
|
| OneClass |
one-class SVM. All the training data are from the same class, SVM builds a boundary that separates the class from the rest of the feature space
|
| value__ |
See Also