Machine Learning 之 LOF离群点检验

来源：互联网发布：网络小胖学生表情包编辑：程序博客网时间：2024/05/21 08:00
#coding=utf-8#本质是基于密度的检测 缺点：计算量巨大#优化 重复点计算import mathprint sorted([1,3,2])[:1],[1,3,2][1:]class LOF:    def __init__(self,data,k,threshold):        self.data=data        self.k=k        self.threshold=threshold        self.outliners=[]    def __calDistance(self,a,b):        sum1=0        for k in range(len(a)):            sum1+=((a[k]-b[k])**2)        sum1=math.sqrt(sum1)        if sum1==0:            sum1=0.00000001        return sum1    def __calNk(self,point):        Nk=[]        disList=[]        for j in range(len(self.data)):            dis=self.__calDistance(point,self.data[j])            disList.append([dis,data[j]])        distList=sorted(distList)        distance=distList[k-1][0]        distList=distList[0:k-1]        disList2=[]        for di in distList[k-1:]:            if di[0]==distList[k-1][0]:                disList2.append(di)        Nk=distList+disList2        Nk=[nk[1] for nk in Nk]        return Nk,distance    def __getReachDis(self,point,Nk):        reachDis=[]        for nk in Nk:            Nk1,dis1=self.__calNk(point)            dis2=self.__calNk(point,nk)            reachDis.append(max(distance,distance2))        return reachDis    def __getLrd(self,point):        Nk,distance=self.__calNk(point)        reachDis=self.__getReachDis(point,Nk)        lrdPoint=1.0*sum(reachDis)/len(reachDis)        return lrdPoint,Nk    def __getLrdList(self,num):        lrdList=[]        lrdPoint,Nk=self.__getLrd(self.data[num])        for l in range(len(Nk)):            lr,=self.__getLrd(Nk(l))            lrdList.append(lr)        return lrdPoint,lrdList    def __getLOF(self,num):        lrdPoint,lrdList=self.__getLrdList(num)        lofValue=0        for lrd in lrdList:            lofValue+=1.0*(lrd/lrdPoint)        lofValue=lofValue/len(lrdList)        return self.data[i],lofValue    def run(self):        for i in range(len(data)):            lofP,lofV=self.__getLOF(i)            if lofV>self.threshold:                self.outliners.append(lofP)        self.outliners=list[(self.outliners)]        return self.outliners
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