RTrees

Objective-C

@interface RTrees : DTrees

Swift

class RTrees : DTrees

The class implements the random forest predictor.

See

REF: ml_intro_rtrees

Member of Ml

Methods

  • Returns the variable importance array. The method returns the variable importance vector, computed at the training stage when CalculateVarImportance is set to true. If this flag was set to false, the empty matrix is returned.

    Declaration

    Objective-C

    - (nonnull Mat *)getVarImportance;

    Swift

    func getVarImportance() -> Mat

  • Creates the empty model. Use StatModel::train to train the model, StatModel::train to create and train the model, Algorithm::load to load the pre-trained model.

    Declaration

    Objective-C

    + (nonnull RTrees *)create;

    Swift

    class func create() -> RTrees

  • Loads and creates a serialized RTree from a file

    Use RTree::save to serialize and store an RTree to disk. Load the RTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier

    Declaration

    Objective-C

    + (nonnull RTrees *)load:(nonnull NSString *)filepath
                nodeName:(nonnull NSString *)nodeName;

    Swift

    class func load(filepath: String, nodeName: String) -> RTrees

    Parameters

    filepath

    path to serialized RTree
    nodeName

    name of node containing the classifier

  • Loads and creates a serialized RTree from a file

    Use RTree::save to serialize and store an RTree to disk. Load the RTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier

    Declaration

    Objective-C

    + (nonnull RTrees *)load:(nonnull NSString *)filepath;

    Swift

    class func load(filepath: String) -> RTrees

    Parameters

    filepath

    path to serialized RTree

  • See

    -setTermCriteria:

    Declaration

    Objective-C

    - (nonnull TermCriteria *)getTermCriteria;

    Swift

    func getTermCriteria() -> TermCriteria

  • See

    -setCalculateVarImportance:

    Declaration

    Objective-C

    - (BOOL)getCalculateVarImportance;

    Swift

    func getCalculateVarImportance() -> Bool

  • See

    -setActiveVarCount:

    Declaration

    Objective-C

    - (int)getActiveVarCount;

    Swift

    func getActiveVarCount() -> Int32

  • Returns the result of each individual tree in the forest. In case the model is a regression problem, the method will return each of the trees’ results for each of the sample cases. If the model is a classifier, it will return a Mat with samples + 1 rows, where the first row gives the class number and the following rows return the votes each class had for each sample.

    Declaration

    Objective-C

    - (void)getVotes:(nonnull Mat *)samples
         results:(nonnull Mat *)results
           flags:(int)flags;

    Swift

    func getVotes(samples: Mat, results: Mat, flags: Int32)

    Parameters

    samples

    Array containing the samples for which votes will be calculated.
    results

    Array where the result of the calculation will be written.
    flags

    Flags for defining the type of RTrees.

  • getActiveVarCount - see: -getActiveVarCount:

    Declaration

    Objective-C

    - (void)setActiveVarCount:(int)val;

    Swift

    func setActiveVarCount(val: Int32)

  • getCalculateVarImportance - see: -getCalculateVarImportance:

    Declaration

    Objective-C

    - (void)setCalculateVarImportance:(BOOL)val;

    Swift

    func setCalculateVarImportance(val: Bool)

  • getTermCriteria - see: -getTermCriteria:

    Declaration

    Objective-C

    - (void)setTermCriteria:(nonnull TermCriteria *)val;

    Swift

    func setTermCriteria(val: TermCriteria)