# Regression random forest and highly skewed response distribution

There is a great deal of information on how unbalanced data sets may impact predictive accuracy in classification problems. Several solutions have been proposed (see here). My questions are:

1. Can a highly skewed target distribution (i.e. when the response variable is continuous and not categorical) create similar problems in a regression random forest? The response I am trying to predict is expressed as a percentage and 96% of the observations take on the value 0.

2. I am using 5-fold cross-validation to estimate RMSE and $R^2$. Is any of these metrics influenced by the response distribution?

3. If the skewed distribution is a problem, how should I deal with it?