| DTrees Class |
Decision Trees
Inheritance HierarchyNamespace: Emgu.CV.ML
Assembly: Emgu.CV.ML (in Emgu.CV.ML.dll) Version: 3.0.0.2161 (3.0.0.2161)
SyntaxThe DTrees type exposes the following members.
ConstructorsMethods| Name | Description | |
|---|---|---|
 | Dispose |
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.) |
 | DisposeObject |
Release the decision tree and all the memory associate with it
(Overrides DisposableObjectDisposeObject.) |
| Equals | (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.) |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
| ReleaseManagedResources |
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.) |
| ToString | Returns a string that represents the current object. (Inherited from Object.) |
Extension Methods| Name | Description | |
|---|---|---|
 | Clear |
Clear the statistic model
(Defined by StatModelExtensions.) |
| Predict |
Predicts response(s) for the provided sample(s)
(Defined by StatModelExtensions.) |
| Read |
Reads algorithm parameters from a file storage.
(Defined by AlgorithmExtensions.) |
| Save |
Save the statistic model to file
(Defined by StatModelExtensions.) |
| Train(TrainData, Int32) | Overloaded.
Trains the statistical model.
(Defined by StatModelExtensions.) |
| Train(IInputArray, DataLayoutType, IInputArray) | Overloaded.
Trains the statistical model.
(Defined by StatModelExtensions.) |
| Write |
Stores algorithm parameters in a file storage
(Defined by AlgorithmExtensions.) |
Fields| Name | Description | |
|---|---|---|
 | _ptr |
A pointer to the unmanaged object
(Inherited from UnmanagedObject.) |
Properties| Name | Description | |
|---|---|---|
 | CVFolds |
If CVFolds greater than 1 then algorithms prunes the built decision tree using K-fold
|
| MaxCategories |
Cluster possible values of a categorical variable into K less than or equals maxCategories clusters to find a suboptimal split
|
| MaxDepth |
The maximum possible depth of the tree
|
| MinSampleCount |
If the number of samples in a node is less than this parameter then the node will not be split
|
| Ptr |
Pointer to the unmanaged object
(Inherited from UnmanagedObject.) |
| RegressionAccuracy |
Termination criteria for regression trees
|
| TruncatePrunedTree |
If true then pruned branches are physically removed from the tree
|
| Use1SERule |
If true then a pruning will be harsher
|
| UseSurrogates |
If true then surrogate splits will be built
|
See Also