OpenCV 2.4.2

org.opencv.ml
Class CvDTree

java.lang.Object
  extended by org.opencv.ml.CvStatModel
      extended by org.opencv.ml.CvDTree

public class CvDTree
extends CvStatModel

The class implements a decision tree as described in the beginning of this section.

See Also:
org.opencv.ml.CvDTree : public CvStatModel

Field Summary
 
Fields inherited from class org.opencv.ml.CvStatModel
nativeObj
 
Constructor Summary
  CvDTree()
           
protected CvDTree(long addr)
           
 
Method Summary
 void clear()
           
protected  void finalize()
           
 Mat getVarImportance()
          Returns the variable importance array.
 boolean train(Mat trainData, int tflag, Mat responses)
          Trains a decision tree.
 boolean train(Mat trainData, int tflag, Mat responses, Mat varIdx, Mat sampleIdx, Mat varType, Mat missingDataMask, CvDTreeParams params)
          Trains a decision tree.
 
Methods inherited from class org.opencv.ml.CvStatModel
load, load, save, save
 
Methods inherited from class java.lang.Object
clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

CvDTree

public CvDTree()

CvDTree

protected CvDTree(long addr)
Method Detail

clear

public void clear()

finalize

protected void finalize()
                 throws java.lang.Throwable
Overrides:
finalize in class CvStatModel
Throws:
java.lang.Throwable

getVarImportance

public Mat getVarImportance()

Returns the variable importance array.

See Also:
org.opencv.ml.CvDTree.getVarImportance

train

public boolean train(Mat trainData,
                     int tflag,
                     Mat responses)

Trains a decision tree.

There are four train methods in "CvDTree":

The function is parallelized with the TBB library.

Parameters:
trainData - a trainData
tflag - a tflag
responses - a responses
See Also:
org.opencv.ml.CvDTree.train

train

public boolean train(Mat trainData,
                     int tflag,
                     Mat responses,
                     Mat varIdx,
                     Mat sampleIdx,
                     Mat varType,
                     Mat missingDataMask,
                     CvDTreeParams params)

Trains a decision tree.

There are four train methods in "CvDTree":

The function is parallelized with the TBB library.

Parameters:
trainData - a trainData
tflag - a tflag
responses - a responses
varIdx - a varIdx
sampleIdx - a sampleIdx
varType - a varType
missingDataMask - a missingDataMask
params - a params
See Also:
org.opencv.ml.CvDTree.train

Official OpenCV 2.4 Documentation