OpenCV学习笔记:opencv_ml模块

一,简介

该模块为opencv的机器学习(machine learning,ml)代码库,包含各种机器学习算法:

0, class CvStatModel ; class CvMLData; struct CvParamGrid;

1,bayesian,Normal Bayes Classifier(贝叶斯分类);

2,K-Nearest Neighbour Classifier(K-邻近算法);

3,SVM,support vector machine(支持向量机);

4,Expectation - Maximization (EM算法);

5,Decision Tree(决策树);

6,Random Trees Classifier(随机森林算法);

7,Extremely randomized trees Classifier(绝对随机森林算法);

8, Boosted tree classifier (Boost树算法);

9,Gradient Boosted Trees (梯度Boost树算法);

10,ANN,Artificial Neural Networks(人工神经网络);

二,分析

namespace cv

{



typedef CvStatModel StatModel;

typedef CvParamGrid ParamGrid;

typedef CvNormalBayesClassifier NormalBayesClassifier;

typedef CvKNearest KNearest;

typedef CvSVMParams SVMParams;

typedef CvSVMKernel SVMKernel;

typedef CvSVMSolver SVMSolver;

typedef CvSVM SVM;

typedef CvDTreeParams DTreeParams;

typedef CvMLData TrainData;

typedef CvDTree DecisionTree;

typedef CvForestTree ForestTree;

typedef CvRTParams RandomTreeParams;

typedef CvRTrees RandomTrees;

typedef CvERTreeTrainData ERTreeTRainData;

typedef CvForestERTree ERTree;

typedef CvERTrees ERTrees;

typedef CvBoostParams BoostParams;

typedef CvBoostTree BoostTree;

typedef CvBoost Boost;

typedef CvANN_MLP_TrainParams ANN_MLP_TrainParams;

typedef CvANN_MLP NeuralNet_MLP;

typedef CvGBTreesParams GradientBoostingTreeParams;

typedef CvGBTrees GradientBoostingTrees;



template<> CV_EXPORTS void Ptr<CvDTreeSplit>::delete_obj();



CV_EXPORTS bool initModule_ml(void);

}

 

三,总结

opencv_ml模块中包含一些常见的机器学习算法,集成了一些目前比较优秀的算法库如libsvm等。不仅可以用于图像,也可以用于其他问题中。

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