AdaBoost和概率神经网络matlab代码

以下是AdaBoost和概率神经网络的MATLAB代码示例：

AdaBoost代码示例：

% 加载数据
load fisheriris;

% 将数据分为训练集和测试集
trainIdx = 1:2:size(meas, 1);
testIdx = 2:2:size(meas, 1);
trainData = meas(trainIdx,:);
trainLabels = species(trainIdx,:);
testData = meas(testIdx,:);
testLabels = species(testIdx,:);

% 训练AdaBoost分类器
numTrees = 50;
model = fitensemble(trainData, trainLabels, 'AdaBoostM1', numTrees, 'Tree');

% 在测试集上进行预测
predLabels = predict(model, testData);

% 计算准确率
accuracy = sum(predLabels == testLabels) / numel(testLabels);
disp(['Accuracy: ' num2str(accuracy)]);

概率神经网络代码示例：

% 加载数据
load iris_dataset;
x = irisInputs;
t = irisTargets;

% 将数据分为训练集和测试集
trainIdx = 1:2:size(x, 2);
testIdx = 2:2:size(x, 2);
xTrain = x(:,trainIdx);
tTrain = t(:,trainIdx);
xTest = x(:,testIdx);
tTest = t(:,testIdx);

% 创建概率神经网络
net = feedforwardnet([10 5]);

% 设置训练参数
net.trainParam.epochs = 100;
net.trainParam.lr = 0.01;
net.trainParam.goal = 0.01;

% 训练概率神经网络
net = train(net, xTrain, tTrain);

% 在测试集上进行预测
y = net(xTest);

% 计算准确率
[~,predLabels] = max(y);
[~,trueLabels] = max(tTest);
accuracy = sum(predLabels == trueLabels) / numel(trueLabels);
disp(['Accuracy: ' num2str(accuracy)]);