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Andre Silva
Andre Silva
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How to deal Dealing with outliers in dependent variables?

boxplot of whole data Here is the boxplot of whole data:

enter image description here

The data is about predicting the number of visitors  (Locals, Foreigners, Total visitors, i.e locals+foreignersLocals + 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.

How to deal with outliers in dependent variables

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.

Dealing with outliers in dependent variables?

Here is the boxplot of whole data:

enter image description here

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.

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Rohit Sharma
Rohit Sharma

How to deal with outliers in dependent variables

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.