目前了解到的MATLAB中分类器有:K近邻分类器,随机森林分类器,朴素贝叶斯,集成学习方法,鉴别分析分类器,支持向量机。现将其主要函数使用方法总结如下,更多细节需参考MATLAB 设 训练样本:train_data 训练样本标签:train_label 测试样本:test_data 测试样本标签:test_label K近邻分类器 mdl = ClassificationKNN.fit(train_data,train_label,'NumNeighbors',1); predict_label accuracy 随机森林分类器(Random Forest) B = TreeBagger(nTree,train_data,train_label); predict_label = predict(B,test_data); 朴素贝叶斯 nb = NaiveBayes.fit(train_data, train_label); predict_label accuracy 集成学习方法(Ensembles for Boosting, Bagging, or Random Subspace) ens = fitensemble(train_data,train_label,'AdaBoostM1' ,100,'tree','type','classification'); predict_label 鉴别分析分类器(discriminant analysis classifier) obj = ClassificationDiscrimina predict_label 支持向量机(Support Vector Machine, SVM) SVMStruct = svmtrain(train_data, train_label); predict_label |
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