EEUC代码matlab

我不确定你具体指的是什么EEUC代码，因为EEUC可能指的是不同的内容。但是，我可以给你一些EEUC相关的Matlab代码示例：

1. 实现EEUC算法的Matlab代码：

function [P, R, F] = EEUC(target, output, weight)
% target: ground truth labels
% output: predicted labels
% weight: class weights

if nargin < 3
    weight = ones(1, max(target));
end

Nc = max(target);
N = length(target);

TP = zeros(Nc, 1);
TN = zeros(Nc, 1);
FP = zeros(Nc, 1);
FN = zeros(Nc, 1);

for i = 1:Nc
    TP(i) = sum(target == i & output == i);
    TN(i) = sum(target ~= i & output ~= i);
    FP(i) = sum(target ~= i & output == i);
    FN(i) = sum(target == i & output ~= i);
end

P = sum(TP .* weight) / (sum(TP .* weight) + sum(FP .* weight));
R = sum(TP .* weight) / (sum(TP .* weight) + sum(FN .* weight));
F = 2 * P * R / (P + R);
end

2. 使用EEUC算法进行分类的Matlab代码：

data = load('data.mat');
X_train = data.X_train;
Y_train = data.Y_train;
X_test = data.X_test;
Y_test = data.Y_test;

% Train the model
model = fitcsvm(X_train, Y_train, 'KernelFunction', 'rbf', 'KernelScale', 0.5, 'ClassNames', [0, 1]);

% Predict the labels of test data
Y_pred = predict(model, X_test);

% Compute the EEUC metrics
[P, R, F] = EEUC(Y_test, Y_pred, [1, 1]);
fprintf('EEUC Precision: %f, Recall: %f, F1 Score: %f\n', P, R, F);

这段代码使用了fitcsvm函数来训练一个支持向量机分类器，并使用EEUC算法来评估分类器的性能。

希望以上代码能够帮助到你。