Decision Tree
Declaration Syntax Members| All Members | Constructors | Methods | Properties | Fields | |
| Icon | Member | Description |
|---|---|---|
 | DTree()()() |
Create a default decision tree
|
 | _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 the decision tree and all the memory associate with it
(Overrides DisposableObject.DisposeObject()()().) |
| Equals(Object) | (Inherited from Object.) |
| Finalize()()() |
Destructor
(Inherited from DisposableObject.) |
| GetHashCode()()() | Serves as a hash function for a particular type. (Inherited from Object.) |
| GetType()()() | Gets the Type of the current instance. (Inherited from Object.) |
| 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>)>), Matrix<(Of <(Int32>)>), Boolean) |
The method takes the feature vector and the optional missing measurement mask on input, traverses the decision tree and returns the reached leaf node on output. The prediction result, either the class label or the estimated function value, may be retrieved as value field of the CvDTreeNode structure
|
 | Ptr |
Pointer to the unmanaged object
(Inherited from UnmanagedObject.) |
| Save(String) |
Save the statistic model to file
(Inherited from StatModel.) |
| ToString()()() | (Inherited from Object.) |
| Train(Matrix<(Of <(Single>)>), DATA_LAYOUT_TYPE, Matrix<(Of <(Single>)>), Matrix<(Of <(Int32>)>), Matrix<(Of <(Int32>)>), Matrix<(Of <(Int32>)>), Matrix<(Of <(Int32>)>), MCvDTreeParams) |
Train the decision tree using the specific traning data
|
Inheritance Hierarchy