OpenCV  3.0.0
Open Source Computer Vision
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Classes | Enumerations | Functions
cv::ml Namespace Reference

Classes

class  ANN_MLP
 Artificial Neural Networks - Multi-Layer Perceptrons. More...
 
class  Boost
 Boosted tree classifier derived from DTrees. More...
 
class  DTrees
 The class represents a single decision tree or a collection of decision trees. More...
 
class  EM
 The class implements the Expectation Maximization algorithm. More...
 
class  KNearest
 The class implements K-Nearest Neighbors model. More...
 
class  LogisticRegression
 Implements Logistic Regression classifier. More...
 
class  NormalBayesClassifier
 Bayes classifier for normally distributed data. More...
 
class  ParamGrid
 The structure represents the logarithmic grid range of statmodel parameters. More...
 
class  RTrees
 The class implements the random forest predictor. More...
 
class  StatModel
 Base class for statistical models in OpenCV ML. More...
 
class  SVM
 Support Vector Machines. More...
 
class  TrainData
 Class encapsulating training data. More...
 

Enumerations

enum  ErrorTypes {
  TEST_ERROR = 0,
  TRAIN_ERROR = 1
}
 Error types More...
 
enum  SampleTypes {
  ROW_SAMPLE = 0,
  COL_SAMPLE = 1
}
 Sample types. More...
 
enum  VariableTypes {
  VAR_NUMERICAL =0,
  VAR_ORDERED =0,
  VAR_CATEGORICAL =1
}
 Variable types. More...
 

Functions

void createConcentricSpheresTestSet (int nsamples, int nfeatures, int nclasses, OutputArray samples, OutputArray responses)
 Creates test set. More...
 
void randGaussMixture (InputArray means, InputArray covs, InputArray weights, int nsamples, OutputArray samples, OutputArray sampClasses)
 Generates sample from gaussian mixture distribution. More...
 
void randMVNormal (InputArray mean, InputArray cov, int nsamples, OutputArray samples)
 Generates sample from multivariate normal distribution. More...