Click or drag to resize

Boost Class

Boosted tree classifier derived from DTrees
Inheritance Hierarchy

Namespace:  OpenCvSharp.ML
Assembly:  OpenCvSharp (in OpenCvSharp.dll) Version: 1.0.0
Syntax
public class Boost : DTrees

The Boost type exposes the following members.

Constructors
  NameDescription
Protected methodBoost
Creates instance by raw pointer cv::ml::Boost*
Top
Properties
  NameDescription
Protected propertyAllocatedMemory
Gets or sets a memory address allocated by AllocMemory.
(Inherited from DisposableObject.)
Protected propertyAllocatedMemorySize
Gets or sets the byte length of the allocated memory
(Inherited from DisposableObject.)
Public propertyBoostType
Type of the boosting algorithm. See Boost::Types. Default value is Boost::REAL.
Public propertyCVFolds
If CVFolds \> 1 then algorithms prunes the built decision tree using K-fold cross-validation procedure where K is equal to CVFolds. Default value is 10.
(Inherited from DTrees.)
Public propertyCvPtr
Native pointer of OpenCV structure
(Inherited from DisposableCvObject.)
Protected propertyDataHandle
Gets or sets a handle which allocates using cvSetData.
(Inherited from DisposableObject.)
Public propertyEmpty
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
(Inherited from Algorithm.)
Public propertyIsDisposed
Gets a value indicating whether this instance has been disposed.
(Inherited from DisposableObject.)
Public propertyIsEnabledDispose
Gets or sets a value indicating whether you permit disposing this instance.
(Inherited from DisposableObject.)
Public propertyMaxCategories
Cluster possible values of a categorical variable into K < =maxCategories clusters to find a suboptimal split.
(Inherited from DTrees.)
Public propertyMaxDepth
The maximum possible depth of the tree.
(Inherited from DTrees.)
Public propertyMinSampleCount
If the number of samples in a node is less than this parameter then the node will not be split. Default value is 10.
(Inherited from DTrees.)
Public propertyPriors
The array of a priori class probabilities, sorted by the class label value.
(Inherited from DTrees.)
Public propertyRegressionAccuracy
Termination criteria for regression trees. If all absolute differences between an estimated value in a node and values of train samples in this node are less than this parameter then the node will not be split further. Default value is 0.01f.
(Inherited from DTrees.)
Public propertyTruncatePrunedTree
If true then pruned branches are physically removed from the tree. Otherwise they are retained and it is possible to get results from the original unpruned (or pruned less aggressively) tree. Default value is true.
(Inherited from DTrees.)
Public propertyUse1SERule
If true then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. Default value is true.
(Inherited from DTrees.)
Public propertyUseSurrogates
If true then surrogate splits will be built. These splits allow to work with missing data and compute variable importance correctly. Default value is false.
(Inherited from DTrees.)
Public propertyWeakCount
The number of weak classifiers. Default value is 100.
Public propertyWeightTrimRate
A threshold between 0 and 1 used to save computational time. Samples with summary weight \f$\leq 1 - weight_trim_rate do not participate in the *next* iteration of training. Set this parameter to 0 to turn off this functionality. Default value is 0.95.
Top
Methods
  NameDescription
Protected methodAllocGCHandle
Pins the object to be allocated by cvSetData.
(Inherited from DisposableObject.)
Protected methodAllocMemory
Allocates the specified size of memory.
(Inherited from DisposableObject.)
Public methodCalcError
Computes error on the training or test dataset
(Inherited from StatModel.)
Public methodStatic memberCreate
Creates the empty model.
Public methodDispose
Releases the resources
(Inherited from DisposableObject.)
Protected methodDispose(Boolean)
Releases the resources
(Inherited from DisposableObject.)
Protected methodDisposeManaged
Releases managed resources
(Overrides DTreesDisposeManaged.)
Protected methodDisposeUnmanaged
releases unmanaged resources
(Inherited from DisposableCvObject.)
Public methodEmpty
(Inherited from StatModel.)
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Destructor
(Inherited from DisposableObject.)
Public methodGetDefaultName
Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.
(Inherited from Algorithm.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetNodes
Returns all the nodes. all the node indices are indices in the returned vector
(Inherited from DTrees.)
Public methodGetRoots
Returns indices of root nodes
(Inherited from DTrees.)
Public methodGetSplits
Returns all the splits. all the split indices are indices in the returned vector
(Inherited from DTrees.)
Public methodGetSubsets
Returns all the bitsets for categorical splits. Split::subsetOfs is an offset in the returned vector
(Inherited from DTrees.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodGetVarCount
Returns the number of variables in training samples
(Inherited from StatModel.)
Public methodIsClassifier
Returns true if the model is classifier
(Inherited from StatModel.)
Public methodIsTrained
Returns true if the model is trained
(Inherited from StatModel.)
Public methodStatic memberLoad
Loads and creates a serialized model from a file.
Public methodStatic memberLoadFromString
Loads algorithm from a String.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Protected methodNotifyMemoryPressure
Notifies the allocated size of memory.
(Inherited from DisposableObject.)
Public methodPredict
Predicts response(s) for the provided sample(s)
(Inherited from StatModel.)
Public methodRead
Reads algorithm parameters from a file storage
(Inherited from Algorithm.)
Public methodSave
Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage fs).
(Inherited from Algorithm.)
Public methodThrowIfDisposed
If this object is disposed, then ObjectDisposedException is thrown.
(Inherited from DisposableObject.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Public methodTrain(TrainData, Int32)
Trains the statistical model
(Inherited from StatModel.)
Public methodTrain(InputArray, SampleTypes, InputArray)
Trains the statistical model
(Inherited from StatModel.)
Public methodWrite
Stores algorithm parameters in a file storage
(Inherited from Algorithm.)
Top
Fields
  NameDescription
Protected fieldptr
Data pointer
(Inherited from DisposableCvObject.)
Top
See Also