| Boost Class |
Boost Tree
Inheritance HierarchyNamespace: Emgu.CV.ML
Assembly: Emgu.CV.World (in Emgu.CV.World.dll) Version: 3.3.0.2824 (3.3.0.2824)
SyntaxThe Boost type exposes the following members.
ConstructorsProperties| 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
|
Methods| Name | Description | |
|---|---|---|
 | Dispose |
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.) |
 | DisposeObject |
Release the Boost classifier and all memory associate with it
(Overrides DisposableObjectDisposeObject.) |
| Equals | (Inherited from Object.) |
| Finalize |
Destructor
(Inherited from DisposableObject.) |
| GetHashCode | (Inherited from Object.) |
| GetType | (Inherited from Object.) |
| MemberwiseClone | (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 | (Inherited from Object.) |
Fields| Name | Description | |
|---|---|---|
 | _ptr |
A pointer to the unmanaged object
(Inherited from UnmanagedObject.) |
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.) |
See Also