I'm using the root mean squared error (RMSE) as a metric for tuning the parameters of my model in a regression problem through cross-validation. However, I'm not so much interested that all predictions are good, I want that about 20% or 40% percent of my predictions are "spot-on" and don't care if the other 80% or 60% are garbage.

What metric would be best for this?

I'm using the root mean squared error (RMSE) as a metric for tuning the parameters of my model in a regression problem through cross-validation. However, I'm not so much interested that all predictions are good, I want that about 20% or 40% percent of my predictions to be "spot-on" and don't care if the other 80% or 60% are garbage.

What metric would be best for this?

I'm using the root mean squared error (RMSE) as a metric for tuning the parameters of my model in a regression problem. However, I'm not so much interested that all predictions are good, I want that about 20% or 40% percent of my predictions are "spot-on" and don't care if the other 80% or 60% are garbage.

What metric would be best for this?

I'm using the root mean squared error (RMSE) as a metric for tuning the parameters of my model in a regression problem through cross-validation. However, I'm not so much interested that all predictions are good, I want that about 20% or 40% percent of my predictions are "spot-on" and don't care if the other 80% or 60% are garbage.

What metric would be best for this?