0413学习笔记：实施kNN算法-构建分类器程序

def classify0(inX, dataSet, labels, k): #inX is input vector, dataSet is training set
    dataSetSize = dataSet.shape[0] #calculate distance
    diffMat = tile(inX, (dataSetSize,1)) - dataSet
    sqDiffMat = diffMat ** 2
    sqDistances = sqDiffMat.sum(axis=1)
    distance = sqDistances ** 0.5
    sortedDistIndicies = distance.argsort()
    classCount = {}
    for i in range(k):
        voteIlabel = labels[sortedDistIndicies[i]]
        classCount[voteIlabel] = classCount.get(voteIlabel,0) + 1
    sortedClassCount = sorted(classCount.iteritems(),
                              key = operator.itemgetter(1),reverse = True)
    return sortedClassCount[0][0]def classify0(inX, dataSet, labels, k): #inX is