python AGNES算法 代码

以下是使用Python实现AGNES算法的示例代码：

import numpy as np

def agnes(X, k):
    n = X.shape[0]
    # 初始化，将每个样本看作一个簇
    clusters = [[i] for i in range(n)]
    # 计算距离矩阵
    dist_matrix = np.zeros((n, n))
    for i in range(n):
        for j in range(i+1, n):
            dist_matrix[i, j] = dist_matrix[j, i] = np.linalg.norm(X[i] - X[j])
    while len(clusters) > k:
        # 找到距离最近的两个簇
        min_dist = np.inf
        for i in range(len(clusters)):
            for j in range(i+1, len(clusters)):
                dist = 0
                for m in clusters[i]:
                    for n in clusters[j]:
                        dist += dist_matrix[m, n]
                dist /= len(clusters[i]) * len(clusters[j])
                if dist < min_dist:
                    min_dist = dist
                    merge_i, merge_j = i, j
        # 合并簇
        clusters[merge_i] += clusters[merge_j]
        clusters.pop(merge_j)
        # 更新距离矩阵
        for i in range(len(clusters)):
            if i != merge_i:
                dist = 0
                for m in clusters[i]:
                    for n in clusters[merge_i]:
                        dist += dist_matrix[m, n]
                dist /= len(clusters[i]) * len(clusters[merge_i])
                dist_matrix[i, merge_i] = dist_matrix[merge_i, i] = dist
    # 构建聚类结果
    labels = np.zeros(n)
    for i, cluster in enumerate(clusters):
        for j in cluster:
            labels[j] = i
    return labels

其中，X是输入的数据矩阵，k是聚类的簇数。该函数返回一个标签数组，表示每个样本所属的簇。