K-means algorithm C + + implementation

Tag:k-means    Data mining        c++    based on partitioning;

#include <bits/stdc++.h> #define Dimense 10//10 Dimensional data # define N 5005#define MAX 0xffffff#define CLR (a) memset (a,0,    sizeof (a)) using namespace Std;struct point{double dir[dimense]; int belong;}; int num=5000;//Data Volume int k=10;//k center point center[15]; Point Data[n]; Point Save[15][n];int ct[15];    Point Mid, point A[],int Num, {point mid;    CLR (Mid.dir);        for (int ii=0;ii<num;ii++) for (int iii=0;iii<dimense;iii++) {MID.DIR[III]+=A[II].DIR[III];    } for (int iii=0;iii<dimense;iii++) Mid.dir[iii]/=num; return mid;}    Double Dis (point A,point b) {double ret=0;    for (int ii=0;ii<dimense;ii++) {ret+= (A.dir[ii]-b.dir[ii]) * (A.dir[ii]-b.dir[ii]); } return sqrt (ret);}    int Signate (point a) {double tmp=max;    int POS;    for (int ii=0;ii<k;ii++) {if (DIS (a,center[ii]) <tmp) Pos=ii,tmp=dis (A,center[ii]); } return POS;}    Double Rec[n][15];int sig[15];int vis[n];int main () {int i,j;    CLR (VIS);    CLR (CT); Freopen ("In.txT "," R ", stdin);    Freopen ("Out.txt", "w", stdout);    for (i=0;i<num;i++) for (j=0;j<dimense;j++) scanf ("%lf", &data[i].dir[j]);    Srand (Time (NULL));    int tmp,cnt=0;        while (cnt<k) {Tmp=rand ()%num;        if (vis[tmp]) continue;    else vis[tmp]=1,center[cnt++]=data[tmp];        } for (i=0;i<k;i++) {printf ("%d Center:", i+1); for (j=0;j<dimense;j++) {printf ("%lf%c", center[i].dir[j],j==dimense-1? ')        \ n ': ');        }} for (i=0;i<num;i++) {data[i].belong=signate (data[i]);    Save[data[i].belong][ct[data[i].belong]++]=data[i];    } for (i=0;i<k;i++) printf ("Number of%d clusters exactly how many points%d\n", i+1,ct[i]);    for (i=0;i<k;i++) Center[i]=mid (Save[i],ct[i]);        for (i=0;i<k;i++) {printf ("%d centers:", i+1); for (j=0;j<dimense;j++) {printf ("%lf%c", center[i].dir[j],j==dimense-1? ')        \ n ': ');    }} point last[15]; for (i=0;i<k;i++) for (j=0;j<dimense;j++) LAST[I].DIR[J]=CENTER[I].DIR[J];    int bre=1;    int nnn=0;        while (BRE) {nnn++;        bre=0;        CLR (save);        CLR (CT);            for (i=0;i<num;i++) {data[i].belong=signate (data[i]);        Save[data[i].belong][ct[data[i].belong]++]=data[i];        } for (i=0;i<k;i++) printf ("Number of%d clusters exactly how many points%d\n", i+1,ct[i]);        for (i=0;i<k;i++) Center[i]=mid (Save[i],ct[i]);                    for (i=0;i<k;i++) {for (j=0;j<dimense;j++) if (Last[i].dir[j]!=center[i].dir[j]) {                    bre=1;                Break            };        if (bre==1) break;        } for (i=0;i<k;i++) for (j=0;j<dimense;j++) last[i].dir[j]=center[i].dir[j];            for (i=0;i<k;i++) {printf ("%d centers:", i+1); for (j=0;j<dimense;j++) {printf ("%lf%c", center[i].dir[j],j==dimense-1? ')            \ n ': '); }}} for (i=0;i<num;i++) {printF ("%d points of%d clusters \ n", i+1,data[i].belong+1);    } printf ("Number%d\n", nnn); return 0;}

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K-means algorithm C + + implementation