from numpy import *

 import operator

 def createDataSet () :

     group = array([[0.5,0.5],[0.9,0.9],[1.0,1.1],[1.0,1.0],[,],[,0.1]])#创建数组

     labels = ['c','A','A','A','B','B'] #列表

     return group,labels

 def classify0(inX,dataSet,labels,k):

     dataSetSize = dataSet.shape[]     #dataSet[] 中有几个元素  答案是4

     diffMat = tile(inX,(dataSetSize,)) - dataSet

     sqDiffMat = diffMat**    #计算出来距离

     sqDistances = sqDiffMat.sum(axis=) #将一个小数组合并的距离的平方

     distances = sqDistances**0.5  #得到具体的距离

     sortedDistIndicies = distances.argsort() #根据索引值进行排序

     print(sortedDistIndicies)

     classCount = {}

     for i in range(k):

         voteIlabel = labels[sortedDistIndicies[i]]   #取出来最小值

      #   print(voteIlabel)

         classCount[voteIlabel] = classCount.get(voteIlabel,)+ # 记录每组分类的案例数。

     #    print(classCount)

         sortedClassCount = sorted(classCount.items(),key=operator.itemgetter(),reverse = True)  # 按照案例数的大小进行排序。

     return sortedClassCount[][]