Statistics and Machine Learning Toolbox的MATLAB代码
时间: 2024-02-28 17:55:32 浏览: 23
下面是使用Statistics and Machine Learning Toolbox进行回归分析和神经网络建模的MATLAB代码示例:
1. 线性回归分析
```matlab
% 导入数据
data = readtable('data.csv');
x = data(:, 1:end-1);
y = data(:, end);
% 建立线性回归模型
mdl = fitlm(x, y);
% 显示回归模型的统计信息
disp(mdl);
% 绘制残差图
plotResiduals(mdl, 'fitted');
```
2. 神经网络建模
```matlab
% 导入数据
data = readtable('data.csv');
x = data(:, 1:end-1);
y = data(:, end);
% 划分训练集和测试集
[trainInd, valInd, testInd] = dividerand(size(x, 1), 0.6, 0.2, 0.2);
xTrain = x(trainInd, :);
yTrain = y(trainInd, :);
xVal = x(valInd, :);
yVal = y(valInd, :);
xTest = x(testInd, :);
yTest = y(testInd, :);
% 建立神经网络模型
net = fitnet(10);
net.trainParam.showWindow = false; % 不显示训练窗口
net = train(net, xTrain', yTrain');
% 预测测试集结果
yPred = net(xTest');
mse = mean((yPred - yTest').^2);
% 显示预测结果和均方误差
disp(['预测结果:', num2str(yPred)]);
disp(['均方误差:', num2str(mse)]);
```