public static double Correlation(int i, int j, int k, Segment segment)
{
Regression R_ij = new Regression(i, j, segment);
Regression R_ik = new Regression(i, k, segment);
Regression R_jk = new Regression(j, k, segment);
double formular1 = 0, formular2 = 0;
double Cijj = R_ij.MSE(segment);
double Cikk = R_ik.MSE(segment);
double temp = 0; //EU_jk[(F_ji - F_ki)^2]
int count_temp = 0;
for (int u = 0; u < R_jk.Uij.Length; u++)
{
int u_index = R_jk.Uij[u];
if (segment.data[u_index, i] != 0)
{
temp += Math.Pow(R_ij.ExpertScore(segment.data[u_index, i], segment) - R_ik.ExpertScore(segment.data[u_index, i], segment), 2);
count_temp++;
}
}
//temp = temp / R_jk.Uij.Length;
temp = temp / count_temp;
formular1 = Cijj + Cikk - temp;
formular2 = 2 * Math.Sqrt(Cijj * Cikk);
return formular1 / formular2;
}
public static double Prediction(int active_user_id, int item_id, Segment segment)
{
//index of item_id in segment data
int item_id_index = -1;
for (int i = 0; i < segment.item_id.Length; i++)
{
if (Convert.ToInt32(segment.item_id[i].Trim()) == item_id)
{
item_id_index = i;
break;
}
}
for(int a = 0; a < segment.data.rows; a++)
{
if (segment.user_id[a] == active_user_id)
{
List<double> L_MSE_ij = new List<double>(); // i,i: item_id_index
List<int> Ia = new List<int>();// Item id index của active user a
double MSE_Min = -9999;
for (int j = 0; j < segment.data.cols - 1; j++) //Bỏ unknown item
{
if (segment.data[a, j] != 0)
{
Ia.Add(j);
Regression r = new Regression(item_id_index, j, segment);
double MSE_ij = r.MSE(segment);
L_MSE_ij.Add(MSE_ij);
if (MSE_Min == -9999 || MSE_ij < MSE_Min)
MSE_Min = MSE_ij;
}
}
List<double> L_MSE_Diag = new List<double>(); // {C*_i}_jj
double Inv_Sum_MSE_Diag = 0;
foreach (double MSE_ij in L_MSE_ij)
{
double MSE_Diag = MSE_ij - segment.Correlation_Avg * MSE_Min;
L_MSE_Diag.Add(MSE_Diag);
Inv_Sum_MSE_Diag += 1 / MSE_Diag;
}
int[] _Ia = Ia.ToArray();
double[] _L_MSE_Diag = L_MSE_Diag.ToArray();
double predict_ai = 0;
for(int j = 0; j < _Ia.Length; j++)
{
double wji = 1 / (_L_MSE_Diag[j] * Inv_Sum_MSE_Diag);
Regression r = new Regression(item_id_index, _Ia[j], segment);
predict_ai += wji * r.ExpertScore(segment.data[a, _Ia[j]], segment);
}
return predict_ai;
}
}
return 0;
}