matlab BP神经网络

clear

clc

% 准备数据

inputs = rand(10, 100); % 100组输入，每组10个特征

outputs = rand(1, 100); % 100组输出，每组1个输出值

% 将数据分成训练集和测试集

trainRatio = 0.8;

valRatio = 0.1;

testRatio = 0.1;

[trainInd, valInd, testInd] = dividerand(100, trainRatio, valRatio, testRatio);

X_train = inputs(:, trainInd);

y_train = outputs(:, trainInd);

X_test = inputs(:, testInd);

y_test = outputs(:, testInd);

% 创建前馈神经网络

hiddenLayerSize = 10;

net = feedforwardnet(hiddenLayerSize);

% 设置训练、验证和测试数据

net.divideParam.trainRatio = 0.8;

net.divideParam.valRatio = 0.1;

net.divideParam.testRatio = 0.1;

% 训练神经网络

[net, tr] = train(net, X_train, y_train);

% 查看训练结果

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