[boxplot of whole data][1]


  [1]: https://i.sstatic.net/CdgfS.jpg

The data is about predicting the number of visitors(Locals, Foreigners, Total visitors i.e locals+foreigners) in national park given certain parameters like temp, weekday etc.

There are some outliers in the dependent variables(last 3 variables in the plot). Although I have dealt with outliers in independent variables using different measures like removing them, replacing with central tendencies or using knn imputations but I have absolutely no idea how to deal with outliers in dependent variables.

Also which model will be suitable with a data having both numerical and categorical independent variables and continuous dependent variable. I have tried random forest/decision trees and some regression techniques.