Python-kmeans算法实践

import numpy as np#调用一些下面写的子函数模拟实现kmeans的功能def kmeans(x, k, maxIt):        numPoints, numDim = x.shape        dataSet = np.zeros((numPoints, numDim + 1))        dataSet[:, :-1] = x        #centroids = dataSet[np.random.randint(numPoints, size = k), :]        #对于中心点的选择应是以随机的方式，这里选择和上篇例子中同样的中心点为了验证结果。        centroids = dataSet[0:2, :]        centroids[:, -1] = range(1, k+1)        iterations = 0        oldCentroids = None        while not shouldStop(oldCentroids, centroids, iterations, maxIt):            print "iteration； \n", iterations            print "dataSet: \n", dataSet            print "centroids: \n", centroids            oldCentroids = np.copy(centroids)            iterations += 1            updataLabels(dataSet, centroids)            centroids = getCentroids(dataSet, k)        return dataSet#对迭代停止时间的判断函数       def shouldStop(oldCentroids, centroids, iterations, maxIt):    if iterations > maxIt:        return True    return np.array_equal(oldCentroids, centroids) #根据中心点修改类别标签   def updataLabels(dataSet, centroids):    numPoints, numDim = dataSet.shape    for i in range(0, numPoints):        dataSet[i,1] = getLabelFromClosestCentroid(dataSet[i,:1], centroids)#计算得出最近的中心点将标签返回的函数       def getLabelFromClosestCentroid(dataSetRow, centroids):    label = centroids[0, -1];    minDist = np.linalg.norm(dataSetRow - centroids[0, :-1])    for i in range(1, centroids.shape[0]):        dist = np.linalg.norm(dataSetRow - centroids[i, :-1])        if dist < minDist:            minDist = dist            label = centroids[i, -1]    print "minDist： ", minDist    return label #根据均值更新中心点   def getCentroids(dataSet, k):    result = np.zeros((k, dataSet.shape[1]))    for i in range(1, k+1):        oneCluster = dataSet[dataSet[:, -1] == i, :-1]        result[i-1, :-1] = np.mean(oneCluster, axis = 0)        result[i-1, -1] = i    return result#下面是一个例子        x1 = np.array([1,1])x2 = np.array([2,1])x3 = np.array([4,3])x4 = np.array([5,4])testX = np.vstack((x1,x2,x3,x4))result = kmeans(testX, 2, 10)print "final result:"print result

最后的例子和上篇的例子一样，计算结果也相同，是正确的结果。