PNN神经网络分类数据的matlab代码
时间: 2023-07-22 07:06:36 浏览: 54
以下是一个简单的PNN神经网络分类数据的Matlab代码示例:
```matlab
% 读入数据
data = load('data.txt');
X = data(:,1:2)';
Y = data(:,3)';
% 数据归一化
[X_norm, mu, sigma] = zscore(X);
% 将数据拆分为训练集和测试集
[trainInd,valInd,testInd] = dividerand(size(X,2),0.6,0.2,0.2);
x_train = X_norm(:,trainInd);
y_train = Y(trainInd);
x_val = X_norm(:,valInd);
y_val = Y(valInd);
x_test = X_norm(:,testInd);
y_test = Y(testInd);
% 训练PNN神经网络模型
net = newpnn(x_train,y_train);
% 预测测试集数据
y_pred = sim(net,x_test);
% 计算准确率
accuracy = sum(y_pred==y_test)/length(y_test);
% 绘制决策边界
plotDecisionBoundary(x_train, y_train, net);
% 绘制训练集和测试集数据散点图
figure;
hold on;
scatter(x_train(1,:),x_train(2,:),10,y_train,'filled');
scatter(x_test(1,:),x_test(2,:),10,y_pred,'filled','d');
hold off;
% 定义绘制决策边界函数
function plotDecisionBoundary(X,Y,net)
xMin = min(X(1,:));
xMax = max(X(1,:));
yMin = min(X(2,:));
yMax = max(X(2,:));
[xx,yy] = meshgrid(xMin:0.01:xMax,yMin:0.01:yMax);
XGrid = [xx(:) yy(:)]';
YGrid = sim(net,XGrid);
contour(xx,yy,reshape(YGrid,size(xx)),[0.5 0.5],'LineWidth',2);
end
```
其中,`data.txt`是包含输入数据和标签的文件,每行包含两个特征和一个标签。`zscore`函数用于归一化数据,`dividerand`函数用于将数据划分为训练集、验证集和测试集。`newpnn`函数用于创建PNN神经网络模型,`sim`函数用于进行预测。`plotDecisionBoundary`函数用于绘制决策边界。