Here is the boxplot of whole data:
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.