/*
ID:hejiek1
LANG: C
TASK:gift1
*/
#include
#include
#include
FILE *fp;
char **a;
int *b;
int who(int n)
{
int i;
char buf[15];
fscanf(fp,"%s",buf);
for(i=0;i if(!strncmp(buf,a[i],15))
return i;
}
void output(int n){
int i;
fp=fopen("gift1.out","w");
for(i=0;i {
fprintf(fp,"%s %d",a[i],b[i]);
fprintf(fp,"n",n);
}
}
int main (int argc, char const* argv[]) {
int n,i,j,give,m,tmp;
fp=fopen("gift1.in","r");
fscanf(fp,"%d",&n);
b=(int *)malloc(n*sizeof(int));
memset(b,0,sizeof(b));
a=(char**)malloc(n*sizeof(char*));
for(i=0;i a[i]=(char*)malloc(15*sizeof(char));
for(i=0;i fscanf(fp,"%s",a[i]);
while(1)
{
j=who(n);
tmp=fscanf(fp,"%d%d",&give,&m);
if(tmp<=0)break;
if(m!=0)
{
b[j]+=give%m-give;
for(i=0;i {
j=who(n);
b[j]+=give/m;
}
}
}
output(n);
return 0;
}</div>
ID:hejiek1
LANG: C
TASK:gift1
*/
#include
#include
#include
FILE *fp;
char **a;
int *b;
int who(int n)
{
int i;
char buf[15];
fscanf(fp,"%s",buf);
for(i=0;i
return i;
}
void output(int n){
int i;
fp=fopen("gift1.out","w");
for(i=0;i
fprintf(fp,"%s %d",a[i],b[i]);
fprintf(fp,"n",n);
}
}
int main (int argc, char const* argv[]) {
int n,i,j,give,m,tmp;
fp=fopen("gift1.in","r");
fscanf(fp,"%d",&n);
b=(int *)malloc(n*sizeof(int));
memset(b,0,sizeof(b));
a=(char**)malloc(n*sizeof(char*));
for(i=0;i
for(i=0;i
while(1)
{
j=who(n);
tmp=fscanf(fp,"%d%d",&give,&m);
if(tmp<=0)break;
if(m!=0)
{
b[j]+=give%m-give;
for(i=0;i
j=who(n);
b[j]+=give/m;
}
}
}
output(n);
return 0;
}</div>
分析预测模型在机器学习中的应用之线性回归
回归能做任何事情 Continue reading