matlab做随机森林

在MATLAB中，可以使用TreeBagger函数来实现随机森林算法。下面是一个简单的示例代码：

首先，准备训练和测试数据：

load fisheriris

% 随机排列数据
rng(1); % 设置随机数种子，使结果可重复
idx = randperm(size(meas,1));
meas = meas(idx,:);
species = species(idx);

% 划分训练和测试集
numObservations = size(meas,1);
numTraining = floor(0.7*numObservations);
trainingIdx = 1:numTraining;
testIdx = (numTraining+1):numObservations;

然后，使用TreeBagger函数训练随机森林模型：

numTrees = 50; % 森林中树的数量
Mdl = TreeBagger(numTrees, meas(trainingIdx,:), species(trainingIdx), 'Method', 'classification');

接下来，使用predict方法进行预测：

predictedSpecies = predict(Mdl, meas(testIdx,:));

最后，计算分类准确率：

accuracy = sum(strcmp(predictedSpecies, species(testIdx)))/numel(testIdx);
disp(['Classification accuracy: ' num2str(accuracy*100) '%']);

完整代码如下：

load fisheriris

% 随机排列数据
rng(1); % 设置随机数种子，使结果可重复
idx = randperm(size(meas,1));
meas = meas(idx,:);
species = species(idx);

% 划分训练和测试集
numObservations = size(meas,1);
numTraining = floor(0.7*numObservations);
trainingIdx = 1:numTraining;
testIdx = (numTraining+1):numObservations;

% 训练随机森林模型
numTrees = 50; % 森林中树的数量
Mdl = TreeBagger(numTrees, meas(trainingIdx,:), species(trainingIdx), 'Method', 'classification');

% 预测
predictedSpecies = predict(Mdl, meas(testIdx,:));

% 计算准确率
accuracy = sum(strcmp(predictedSpecies, species(testIdx)))/numel(testIdx);
disp(['Classification accuracy: ' num2str(accuracy*100) '%']);