org.opencv.ml
public class CvERTrees extends CvRTrees
The class implements the Extremely randomized trees algorithm.
CvERTrees
is inherited from "CvRTrees" and has the same
interface, so see description of "CvRTrees" class to get details. To set the
training parameters of Extremely randomized trees the same class "CvRTParams"
is used.
Constructor and Description |
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CvERTrees() |
Modifier and Type | Method and Description |
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boolean |
train(Mat trainData,
int tflag,
Mat responses)
Trains the Random Trees model.
|
boolean |
train(Mat trainData,
int tflag,
Mat responses,
Mat varIdx,
Mat sampleIdx,
Mat varType,
Mat missingDataMask,
CvRTParams params)
Trains the Random Trees model.
|
clear, getVarImportance, predict_prob, predict_prob, predict, predict
load, load, save, save
public boolean train(Mat trainData, int tflag, Mat responses)
CvRTrees
Trains the Random Trees model.
The method "CvRTrees.train" is very similar to the method "CvDTree.train"
and follows the generic method "CvStatModel.train" conventions. All the
parameters specific to the algorithm training are passed as a "CvRTParams"
instance. The estimate of the training error (oob-error
) is
stored in the protected class member oob_error
.
The function is parallelized with the TBB library.
train
in class CvRTrees
trainData
- a trainDatatflag
- a tflagresponses
- a responsespublic boolean train(Mat trainData, int tflag, Mat responses, Mat varIdx, Mat sampleIdx, Mat varType, Mat missingDataMask, CvRTParams params)
CvRTrees
Trains the Random Trees model.
The method "CvRTrees.train" is very similar to the method "CvDTree.train"
and follows the generic method "CvStatModel.train" conventions. All the
parameters specific to the algorithm training are passed as a "CvRTParams"
instance. The estimate of the training error (oob-error
) is
stored in the protected class member oob_error
.
The function is parallelized with the TBB library.
train
in class CvRTrees
trainData
- a trainDatatflag
- a tflagresponses
- a responsesvarIdx
- a varIdxsampleIdx
- a sampleIdxvarType
- a varTypemissingDataMask
- a missingDataMaskparams
- a params