机器学习实战-kNN

from numpy import *
import operator

def classify0(inX,dataSet,labels,k):
    dataSetSize=dataSet.shape[0]
    diffMat=tile(inX,(dataSetSize,1))-dataSet
    sqDiffMat=diffMat**2
    sqDistances=sqDiffMat.sum(axis=1)
    distances=sqDistances**0.5
    sortedDisIndicies=distances.argsort()
    classCount={}
    for i in range(k):
        voteIlabel=labels[sortedDisIndicies[i]]
        classCount[voteIlabel]=classCount.get(voteIlabel,0)+1
    sortedClassCount=sorted(classCount.items(),key=operator.itemgetter(1),reverse=True)
    return sortedClassCount

def createDataSet():
    group=array([[1.0,1.1],[1.0,1.0],[0,0],[0,0.1]])
    labels = ['A','A','B','B']
    return group, labels

上面的是代码，第一次用python跟着做，很头疼啊，很多函数需要现查。