Gradient descent algorithm c ++ realize

No data standardized version, the efficiency is very high, and the training results are not good.

#include <the iostream> 
#define MAXN 105 
#include <cstdio> 
the using namespace STD; 
int n-, m; // n-th feature, m data 
double theta [maxn]; // parameter set 
Double TEMP [MAXN]; 
Double Data [maxn] [maxn]; // data set 
double Y [maxn]; // result set 
Double HX [MAXN]; 
const Double EPS = 0.37; 
Double Alpha = 0.00001; 
Double H (int X) // calculations assume functions 
{ 
    RES = 0 Double; 
    for (int I = 0; I <= n-; I ++) 
    { 
        RES Theta + = [I] * Data [X] [I]; 
    } 
    return RES; 
} 
Double J_theta () // calculate the cost of function 
{ 
    Double RES = 0; 
    for (int I =. 1; I <= m; I ++) 
    {
        res+=(h(i)-Y[i])*(h(i)-Y[i]);
    }
    res=res/(2*m);
    return res;
}
double f(int x)//求偏导数
{
    double res=0;
    for(int i=1;i<=m;++i)
    {
        res+=hx[i]*data[i][x];
    }
    res/=m;
    return res;
}
void Gradient_Descent()//梯度下降
{
    for(int i=1;i<=m;++i)
    {
        data[i][0]=1;
    }
    for(int i=0;i<=n;++i)
    {
        theta[i]=1;//初始化
    }
    double now,nex;
    do
    {
        now=J_theta();
        for(int i=1;i<=m;++i)
        {
            hx[i]=h(i)-Y[i];
        }
        for(int i=0;i<=n;++i)
        {
            temp[i]=theta[i]-alpha*f(i);
        }
        for(int i=0;i<=n;++i)
        {
            theta[i]=temp[i];
        }
        nex=J_theta();
        //cout<<J_theta()<<endl;
    }while (J_theta()>eps);
}
int main()
{
    freopen("in.txt","r",stdin);
    cin>>n>>m;
    for(int i=1;i<=m;++i)
    {
        for(int j=1;j<=n;++j)
        {
            cin>>data[i][j];
        }
    }
    for(int i=1;i<=m;++i)
    {
        cin>>Y[i];
    }
    Gradient_Descent();
    for(int i=0;i<=n;++i)
    {
        printf("%.2lf\n",theta[i]);
    }
    return 0;
}