What if var is too small and the loss can be ignored?

Answer 1

If the variance (var) in a dataset is too small, it means that the data points are closely clustered around the mean, leading to reduced variability. In such cases, any potential loss or errors might be negligible, as the predictions or outcomes will likely remain consistent. However, ignoring the loss entirely could lead to oversights in model performance or bias, especially if more data or different scenarios are introduced later. It's essential to balance the consideration of variance and loss to ensure robust decision-making.