最小最大距离法（python实现）

import numpy as np
import random


def minMaxCluster(data, ratio=0.5):
    """
    最小最大距离聚类法

    参数
    --------------
    :param data: 待聚类样本
    :param ratio: 创建新聚类中心的距离系数
    :return: result：聚类标签
    """

    # 计算样本间距离，储存在距离矩阵distanceArray中
    def computerDistance(data):
        distanceArray = np.zeros((data.shape[0], data.shape[0]))
        for i in range(data.shape[0]):
            for j in range(i, data.shape[0]):
                distanceArray[i, j] = np.sum(np.square(data[i] - data[j]))
                distanceArray[j, i] = distanceArray[i, j]
        return distanceArray

    # 初始化2个聚类中心点
    def initialCluster(data, distanceArray):
        cluster1 = random.randint(0, data.shape[0] - 1)
        cluster2 = np.argmax(distanceArray[cluster1])
        clusters = [cluster1, cluster2]
        return clusters