Matlab中常用机器学习函数

更多内容请参考http://cn.mathworks.com/help/stats/index.html?s_cid=doc_ftr。

Naive Bayes（朴素贝叶斯）

Factor = NaiveBayes.fit(train_data, train_label);
Scores = posterior(Factor, test_data);
[Scores,Predict_label] = posterior(Factor, test_data);
Predict_label = predict(Factor, test_data);

 

Random Forest（随机森林）

Factor = TreeBagger(nTree, train_data, train_label);
[Predict_label,Scores] = predict(Factor, test_data);
%scores是语义向量(概率输出)

 

KNN（K近邻分类器）

新版本将无法使用knnclassify

predict_label = knnclassify(test_data, train_data,train_label, num_neighbors);

 

mdl = ClassificationKNN.fit(train_data,train_label,'NumNeighbors',1);
predict_label   =       predict(mdl, test_data);

 

SVM（支持向量机）

matlab自带svm

Factor = svmtrain(train_data, train_label);
predict_label = svmclassify(Factor, test_data);

libsvm

Factor = svmtrain(train_label, train_data, '-b 1');
[predicted_label, accuracy, Scores] = svmpredict(test_label, test_data, Factor, '-b 1');

 

集成学习器（Ensembles for Boosting, Bagging, or Random Subspace）

ens = fitensemble(train_data,train_label,'AdaBoostM1' ,100,'tree','type','classification');
predict_label   =       predict(ens, test_data);

 

鉴别分析分类器（discriminant analysis classifier）

obj = ClassificationDiscriminant.fit(train_data, train_label);
[predict_label, Scores] = predict(Factor, test_data);

 

转载于:https://www.cnblogs.com/MrLancher/p/6217224.html