I am trying to use Lin’s Concordance Correlation Coefficient as loss function but it seems it is not work correctly as the loss value using this cost function does not change meaningfully. Can anyone help me with some advices?
Here is my code:
class ConcordanceCorCoeff(nn.Module):
def __init__(self):
    super(ConcordanceCorCoeff, self).__init__()
    self.mean = torch.mean
    self.var = torch.var
    self.sum = torch.sum
    self.sqrt = torch.sqrt
    self.std = torch.std
def forward(self, prediction, ground_truth):
    mean_gt = self.mean (ground_truth, 0)
    mean_pred = self.mean (prediction, 0)
    var_gt = self.var (ground_truth, 0)
    var_pred = self.var (prediction, 0)
    v_pred = prediction - mean_pred
    v_gt = ground_truth - mean_gt
    cor = self.sum (v_pred * v_gt) / (self.sqrt(self.sum(v_pred ** 2)) * self.sqrt(self.sum(v_gt ** 2)))
    sd_gt = self.std(ground_truth)
    sd_pred = self.std(prediction)
    numerator=2*cor*sd_gt*sd_pred
    denominator=var_gt+var_pred+(mean_gt-mean_pred)**2
    ccc = numerator/denominator
    return 1-ccc