/// <summary>
/// Computes the loss between the expected values (ground truth)
/// and the given actual values that have been predicted.
/// </summary>
/// <param name="actual">The actual values that have been predicted.</param>
/// <returns>
/// The loss value between the expected values and
/// the actual predicted values.
/// </returns>
public override double[] Loss(double[][] actual)
{
int N = actual.Length;
int M = actual.Columns();
int P = NumberOfInputs;
double[] SSe = new double[M];
double[] SSt = new double[M];
double[] r2 = new double[M];
// For each output variable
double[] avg = Expected.WeightedMean(Weights);
// Calculate SSe and SSt
for (int i = 0; i < N; i++)
{
for (int c = 0; c < M; c++)
{
double w = Weights[i];
double d;
d = Expected[i][c] - actual[i][c];
SSe[c] += w * d * d;
d = Expected[i][c] - avg[c];
SSt[c] += w * d * d;
}
}
// Calculate R-Squared
for (int c = 0; c < M; c++)
{
r2[c] = 1 - (((Math.Abs(SSt[c] - SSe[c]) / N) > 1e-16) ? SSe[c] / SSt[c] : 0);
}
if (Adjust)
{
// Return adjusted R-Squared
for (int c = 0; c < M; c++)
{
if (r2[c] == 1.0)
{
continue;
}
if (N == P + 1)
{
r2[c] = double.NaN;
}
else
{
r2[c] = 1.0 - (1.0 - r2[c]) * ((N - 1.0) / (N - P - 1.0));
}
}
}
return(r2);
}
/// <summary>
/// Computes the loss between the expected values (ground truth)
/// and the given actual values that have been predicted.
/// </summary>
/// <param name="actual">The actual values that have been predicted.</param>
/// <returns>
/// The loss value between the expected values and
/// the actual predicted values.
/// </returns>
public double Loss(double[] actual)
{
// R-squared = 100 * SS(regression) / SS(total)
int p = NumberOfInputs;
int n = actual.Length;
double SSe = 0.0;
double SSt = 0.0;
// Calculate output mean
double avg = Expected.WeightedMean(Weights).Mean();
// Calculate SSe and SSt
for (int i = 0; i < Expected.Length; i++)
{
double w = Weights[i];
double d = Expected[i][0] - actual[i];
SSe += w * d * d;
d = Expected[i][0] - avg;
SSt += w * d * d;
}
// Calculate R-Squared
double r2 = 1 - (((Math.Abs(SSt - SSe) / n) > 1e-16) ? SSe / SSt : 0);
if (!Adjust)
{
// Return ordinary R-Squared
return(r2);
}
if (r2 == 1)
{
return(1);
}
if (n - p == 1.0)
{
return(double.NaN);
}
// Return adjusted R-Squared
return(1.0 - (1.0 - r2) * ((n - 1.0) / (n - p - 1.0)));
}
