Package org.opencv.ml

Class DTrees

java.lang.Object
org.opencv.core.Algorithm
org.opencv.ml.StatModel
org.opencv.ml.DTrees
Direct Known Subclasses:
Boost, RTrees
public class DTrees extends StatModel
The class represents a single decision tree or a collection of decision trees. The current public interface of the class allows user to train only a single decision tree, however the class is capable of storing multiple decision trees and using them for prediction (by summing responses or using a voting schemes), and the derived from DTrees classes (such as RTrees and Boost) use this capability to implement decision tree ensembles. SEE: REF: ml_intro_trees

  • Field Details

  • Method Details

    • __fromPtr__

      public static DTrees __fromPtr__(long addr)

    • getMaxCategories

      public int getMaxCategories()
      SEE: setMaxCategories
      Returns:
      automatically generated

    • setMaxCategories

      public void setMaxCategories(int val)
      getMaxCategories SEE: getMaxCategories
      Parameters:
      val - automatically generated

    • getMaxDepth

      public int getMaxDepth()
      SEE: setMaxDepth
      Returns:
      automatically generated

    • setMaxDepth

      public void setMaxDepth(int val)
      getMaxDepth SEE: getMaxDepth
      Parameters:
      val - automatically generated

    • getMinSampleCount

      public int getMinSampleCount()
      SEE: setMinSampleCount
      Returns:
      automatically generated

    • setMinSampleCount

      public void setMinSampleCount(int val)
      getMinSampleCount SEE: getMinSampleCount
      Parameters:
      val - automatically generated

    • getCVFolds

      public int getCVFolds()
      SEE: setCVFolds
      Returns:
      automatically generated

    • setCVFolds

      public void setCVFolds(int val)
      getCVFolds SEE: getCVFolds
      Parameters:
      val - automatically generated

    • getUseSurrogates

      public boolean getUseSurrogates()
      SEE: setUseSurrogates
      Returns:
      automatically generated

    • setUseSurrogates

      public void setUseSurrogates(boolean val)
      getUseSurrogates SEE: getUseSurrogates
      Parameters:
      val - automatically generated

    • getUse1SERule

      public boolean getUse1SERule()
      SEE: setUse1SERule
      Returns:
      automatically generated

    • setUse1SERule

      public void setUse1SERule(boolean val)
      getUse1SERule SEE: getUse1SERule
      Parameters:
      val - automatically generated

    • getTruncatePrunedTree

      public boolean getTruncatePrunedTree()
      SEE: setTruncatePrunedTree
      Returns:
      automatically generated

    • setTruncatePrunedTree

      public void setTruncatePrunedTree(boolean val)
      getTruncatePrunedTree SEE: getTruncatePrunedTree
      Parameters:
      val - automatically generated

    • getRegressionAccuracy

      public float getRegressionAccuracy()
      SEE: setRegressionAccuracy
      Returns:
      automatically generated

    • setRegressionAccuracy

      public void setRegressionAccuracy(float val)
      getRegressionAccuracy SEE: getRegressionAccuracy
      Parameters:
      val - automatically generated

    • getPriors

      public Mat getPriors()
      SEE: setPriors
      Returns:
      automatically generated

    • setPriors

      public void setPriors(Mat val)
      getPriors SEE: getPriors
      Parameters:
      val - automatically generated

    • create

      public static DTrees create()
      Creates the empty model The static method creates empty decision tree with the specified parameters. It should be then trained using train method (see StatModel::train). Alternatively, you can load the model from file using Algorithm::load<DTrees>(filename).
      Returns:
      automatically generated

    • load

      public static DTrees load(String filepath, String nodeName)
      Loads and creates a serialized DTrees from a file Use DTree::save to serialize and store an DTree to disk. Load the DTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier
      Parameters:
      filepath - path to serialized DTree
      nodeName - name of node containing the classifier
      Returns:
      automatically generated

    • load

      public static DTrees load(String filepath)
      Loads and creates a serialized DTrees from a file Use DTree::save to serialize and store an DTree to disk. Load the DTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier
      Parameters:
      filepath - path to serialized DTree
      Returns:
      automatically generated