用matlab编程给定测试集,计算混淆矩阵、查准率、查全率和FPR
时间: 2023-12-30 18:05:19 浏览: 36
好的,以下是一个用Matlab编写的计算混淆矩阵、查准率、查全率和FPR的示例代码:
```matlab
% 假设预测结果保存在predicted_labels中,真实标签保存在true_labels中
% predicted_labels和true_labels的大小应该相同
num_classes = max(true_labels); % 类别数
confusion_matrix = zeros(num_classes, num_classes); % 初始化混淆矩阵
for i = 1:length(true_labels)
confusion_matrix(true_labels(i), predicted_labels(i)) = confusion_matrix(true_labels(i), predicted_labels(i)) + 1;
end
% 计算查准率、查全率和FPR
precision = zeros(num_classes, 1);
recall = zeros(num_classes, 1);
fpr = zeros(num_classes, 1);
for i = 1:num_classes
tp = confusion_matrix(i, i);
fp = sum(confusion_matrix(:, i)) - tp;
fn = sum(confusion_matrix(i, :)) - tp;
tn = sum(confusion_matrix(:)) - tp - fp - fn;
precision(i) = tp / (tp + fp);
recall(i) = tp / (tp + fn);
fpr(i) = fp / (fp + tn);
end
```
这个代码会输出混淆矩阵、查准率、查全率和FPR。你只需要将预测结果和真实标签传递给代码中的`predicted_labels`和`true_labels`变量即可。