Class Summary 
CvANN_MLP 
MLP model. 
CvANN_MLP_TrainParams 
Parameters of the MLP training algorithm. 
CvBoost 
Boosted tree classifier derived from "CvStatModel". 
CvBoostParams 
Boosting training parameters. 
CvDTree 
The class implements a decision tree as described in the beginning of this
section. 
CvDTreeParams 
The structure contains all the decision tree training parameters. 
CvERTrees 
The class implements the Extremely randomized trees algorithm. 
CvGBTrees 
The class implements the Gradient boosted tree model as described in the
beginning of this section. 
CvGBTreesParams 
GBT training parameters. 
CvKNearest 
The class implements KNearest Neighbors model as described in the beginning
of this section. 
CvNormalBayesClassifier 
Bayes classifier for normally distributed data. 
CvParamGrid 
The structure represents the logarithmic grid range of statmodel parameters. 
CvRTParams 
Training parameters of random trees. 
CvRTrees 
The class implements the random forest predictor as described in the
beginning of this section. 
CvStatModel 
Base class for statistical models in ML. 
CvSVM 
Support Vector Machines. 
CvSVMParams 
SVM training parameters. 
EM 
The class implements the EM algorithm as described in the beginning of this
section. 
Ml 
