DBSCAN聚类算法matlab代码

以下是DBSCAN聚类算法的MATLAB代码示例：

function [clusters, noise] = dbscan(X, epsilon, MinPts)
% DBSCAN聚类算法
% 输入：数据矩阵X，半径epsilon，最小点数MinPts
% 输出：簇集合clusters，噪声点集合noise

% 初始化
n = size(X, 1);
visited = false(n, 1);
clusters = {};
noise = [];

% 计算距离矩阵
D = pdist(X);

% 构建邻接矩阵
A = zeros(n, n);
A(D < epsilon) = 1;

% 开始聚类
for i = 1:n
    if ~visited(i)
        visited(i) = true;
        neighbors = find(A(i, :));
        if length(neighbors) < MinPts
            noise = [noise; i];
        else
            C = [i];
            expandCluster(i, neighbors, C);
            clusters = [clusters; {C}];
        end
    end
end

% 扩展簇
function expandCluster(i, neighbors, C)
    for j = 1:length(neighbors)
        if ~visited(neighbors(j))
            visited(neighbors(j)) = true;
            C = [C neighbors(j)];
            newNeighbors = find(A(neighbors(j), :));
            if length(newNeighbors) >= MinPts
                neighbors = [neighbors newNeighbors];
            end
        end
        if ~ismember(neighbors(j), [C noise])
            C = [C neighbors(j)];
        end
    end
end

end

其中，输入参数X是数据矩阵，epsilon是半径，MinPts是最小点数。函数返回参数clusters是聚类结果，noise是噪声点集合。