Python聚类算法之基本K均值实例详解

# scoding=utf-8import pylab as plpoints = [[int(eachpoint.split("#")[0]), int(eachpoint.split("#")[1])] for eachpoint in open("points","r")]# 指定三个初始质心currentCenter1 = [20,190]; currentCenter2 = [120,90]; currentCenter3 = [170,140]pl.plot([currentCenter1[0]], [currentCenter1[1]],'ok')pl.plot([currentCenter2[0]], [currentCenter2[1]],'ok')pl.plot([currentCenter3[0]], [currentCenter3[1]],'ok')# 记录每次迭代后每个簇的质心的更新轨迹center1 = [currentCenter1]; center2 = [currentCenter2]; center3 = [currentCenter3]# 三个簇group1 = []; group2 = []; group3 = []for runtime in range(50):  group1 = []; group2 = []; group3 = []  for eachpoint in points:    # 计算每个点到三个质心的距离    distance1 = pow(abs(eachpoint[0]-currentCenter1[0]),2) + pow(abs(eachpoint[1]-currentCenter1[1]),2)    distance2 = pow(abs(eachpoint[0]-currentCenter2[0]),2) + pow(abs(eachpoint[1]-currentCenter2[1]),2)    distance3 = pow(abs(eachpoint[0]-currentCenter3[0]),2) + pow(abs(eachpoint[1]-currentCenter3[1]),2)    # 将该点指派到离它最近的质心所在的簇    mindis = min(distance1,distance2,distance3)    if(mindis == distance1):      group1.append(eachpoint)    elif(mindis == distance2):      group2.append(eachpoint)    else:      group3.append(eachpoint)  # 指派完所有的点后，更新每个簇的质心  currentCenter1 = [sum([eachpoint[0] for eachpoint in group1])/len(group1),sum([eachpoint[1] for eachpoint in group1])/len(group1)]  currentCenter2 = [sum([eachpoint[0] for eachpoint in group2])/len(group2),sum([eachpoint[1] for eachpoint in group2])/len(group2)]  currentCenter3 = [sum([eachpoint[0] for eachpoint in group3])/len(group3),sum([eachpoint[1] for eachpoint in group3])/len(group3)]  # 记录该次对质心的更新  center1.append(currentCenter1)  center2.append(currentCenter2)  center3.append(currentCenter3)# 打印所有的点，用颜色标识该点所属的簇pl.plot([eachpoint[0] for eachpoint in group1], [eachpoint[1] for eachpoint in group1], 'or')pl.plot([eachpoint[0] for eachpoint in group2], [eachpoint[1] for eachpoint in group2], 'oy')pl.plot([eachpoint[0] for eachpoint in group3], [eachpoint[1] for eachpoint in group3], 'og')# 打印每个簇的质心的更新轨迹for center in [center1,center2,center3]:  pl.plot([eachcenter[0] for eachcenter in center], [eachcenter[1] for eachcenter in center],'k')pl.show()