DBI算法matlab
时间: 2023-11-02 08:01:39 浏览: 296
DBI算法是一种评估聚类算法的度量指标,用于优化聚类算法中的k值选择。它通过计算类内距离之和与类间距离之比来判断聚类的效果,以避免K-means算法中出现局部最优解的情况。在Matlab中,可以使用以下代码来计算DBI指数:
```matlab
function dbi = calculateDBI(data, labels, centroids)
k = max(labels);
sum_db = 0;
for i = 1:k
intra_cluster_dist = calculateIntraClusterDist(data(labels == i,:), centroids(i,:));
inter_cluster_dist = calculateInterClusterDist(centroids, i);
db = (intra_cluster_dist + inter_cluster_dist) / intra_cluster_dist;
sum_db = sum_db + db;
end
dbi = sum_db / k;
end
function dist = calculateIntraClusterDist(data, centroid)
n = size(data, 1);
dist = sum(sum((data - repmat(centroid, n, 1)).^2, 2)) / n;
end
function dist = calculateInterClusterDist(centroids, cluster_idx)
k = size(centroids, 1);
dist = 0;
for i = 1:k
if i ~= cluster_idx
dist = dist + euclideanDist(centroids(cluster_idx,:), centroids(i,:));
end
end
dist = dist / (k - 1);
end
function dist = euclideanDist(a, b)
dist = sqrt(sum((a - b).^2));
end
```
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