KNN简单实现

KNN（K nearest neighbor Algorithm）

原理：取距离上训练数据上最近的K个点的均值作为估计值。

简单实现：

//A general realization of K nearest neighbors Algorithm#include <iostream> #include <vector>#include <algorithm>#include <cmath>using namespace std; struct ob{   double dis,val;};bool cmp(ob a,ob b){return a.dis<b.dis;}int main(){int K,n,x;cout<<"Please put in the value for parameter K:";cin>>K;cout<<"\nPlease put in the value for attribute amount x:";cin>>x;cout<<"\nPlease put in the value for data amount n:";cin>>n;cout<<"Please put in the data in the form of x1,...,xi,...xn,value repeatly\n";vector <vector<double> > data;for(int i=0;i<n;i++){vector <double> v;double tmp;for(int j=0;j<=x;j++){cin>>tmp;v.push_back(tmp);}data.push_back(v);}cout<<"Please put in the data to be predicted in the form of x1,...,xi,...xn\n";while(1){vector <double> v;double tmp,pred_val=0;for(int i=0;i<x;i++){cin>>tmp;v.push_back(tmp);}vector <ob> q;ob apiece;for(int i=0;i<n;i++){apiece.dis=0;for(int j=0;j<x;j++){apiece.dis+=(v[j]-data[i][j])*(v[j]-data[i][j]);}apiece.dis=sqrt(apiece.dis);apiece.val=data[i][x];q.push_back(apiece);}sort(q.begin(),q.end(),cmp);for(int i=0;i<K;i++){pred_val+=q[i].val;}pred_val/=K;cout<<"The predicted value is :"<<pred_val<<endl;}return 0;}