请帮我编一个对鸢尾花数据集进行加入levy飞行策略的Kmeans聚类的matlab代码

以下是对鸢尾花数据集进行加入levy飞行策略的Kmeans聚类的matlab代码：

% 加载鸢尾花数据集
load fisheriris;

% 设置参数
k = 3; % 聚类数目
maxIter = 100; % 最大迭代次数
tol = 1e-5; % 收敛容差
beta = 1.5; % levy飞行beta参数
alpha = 0.01; % 学习率
m = size(meas,1); % 样本数
n = size(meas,2); % 特征数

% 随机初始化聚类中心
centers = datasample(meas,k,'Replace',false);

% 迭代聚类
for iter = 1:maxIter
% 初始化
prevCenters = centers;
prevCost = 0;
cost = 0;
moved = false(k,1);
counts = zeros(k,1);
s = zeros(k,n);

% 分配样本到聚类
for i = 1:m
minDist = Inf;
minIdx = 0;
for j = 1:k
dist = norm(meas(i,:)-centers(j,:))^2;
if dist < minDist
minDist = dist;
minIdx = j;
end
end
cost = cost + minDist;
counts(minIdx) = counts(minIdx) + 1;
s(minIdx,:) = s(minIdx,:) + meas(i,:);
end

% 更新聚类中心
for j = 1:k
if counts(j) > 0
centers(j,:) = s(j,:) / counts(j);
end
end

% 检查是否收敛
if norm(centers-prevCenters) < tol
break;
end

% 使用levy飞行更新聚类中心
for j = 1:k
if moved(j)
continue;
end
l = levy(beta,n);
r = alpha * l .* (centers(j,:) - prevCenters(j,:));
centers(j,:) = centers(j,:) + r;
moved(j) = true;
end

% 更新学习率
alpha = alpha * 0.99;
end

% 绘制聚类结果
figure;
gscatter(meas(:,1),meas(:,2),species,'rgb','osd');
hold on;
plot(centers(:,1),centers(:,2),'kx','MarkerSize',15,'LineWidth',3);
legend('setosa','versicolor','virginica','Centroids','Location','NW');
title 'K-Means Clustering with Levy Flight Strategy';

% levy飞行函数
function l = levy(beta,n)
u = randn(1,n) .* sqrt(abs(beta ./ (2 * pi .* ugamma(1 + beta/2))));
v = randn(1,n);
l = u ./ (abs(v) .^ (1 / beta));
end