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I want to balance the distribution of data using the ROSE function.

The balance of the data was adjusted, but the value of the independent variable was changed accordingly.

In my data, there was an explanatory variable that shows the customer's income.

Since I performed the ROSE function, I found an observation with a negative number in the income variable.

Income can not be negative, but is this correct?

Here is result of ROSE function.

> str(data.rose)
'data.frame':   700 obs. of  21 variables:
 $ Creditability                    : int  1 1 1 1 1 1 1 1 1 1 ...
 $ Account.Balance                  : Factor w/ 4 levels "1","2","3","4": 1 2 2 4 4 4 4 3 4 1 ...
 $ Duration.of.Credit..month.       : num  2.94 18.52 10.61 23.94 13.14 ...
 $ Payment.Status.of.Previous.Credit: Factor w/ 5 levels "0","1","2","3",..: 5 2 3 5 3 3 5 5 3 3 ...
 $ Purpose                          : Factor w/ 10 levels "0","1","2","3",..: 4 4 3 4 3 2 4 7 1 4 ...
 $ Credit.Amount                    : num  -1082 2370 2675 1860 2055 ...
 $ Value.Savings.Stocks             : Factor w/ 5 levels "1","2","3","4",..: 5 1 4 1 1 5 1 1 1 1 ...
 $ Length.of.current.employment     : Factor w/ 5 levels "1","2","3","4",..: 5 3 2 5 5 5 3 3 3 3 ...
 $ Instalment.per.cent              : Factor w/ 4 levels "1","2","3","4": 4 4 4 4 4 3 4 2 2 4 ...
 $ Sex...Marital.Status             : Factor w/ 4 levels "1","2","3","4": 3 3 2 4 3 3 3 2 3 4 ...
 $ Guarantors                       : Factor w/ 3 levels "1","2","3": 1 1 1 2 1 1 1 1 3 1 ...
 $ Duration.in.Current.address      : Factor w/ 4 levels "1","2","3","4": 4 4 1 3 4 4 2 4 3 2 ...
 $ Most.valuable.available.asset    : Factor w/ 4 levels "1","2","3","4": 1 1 1 1 2 3 2 2 2 1 ...
 $ Age..years.                      : num  71.4 24.5 28.4 55.1 52.9 ...
 $ Concurrent.Credits               : Factor w/ 3 levels "1","2","3": 3 2 3 3 1 3 3 3 3 3 ...
 $ Type.of.apartment                : Factor w/ 3 levels "1","2","3": 2 2 2 2 2 2 2 2 1 2 ...
 $ No.of.Credits.at.this.Bank       : Factor w/ 4 levels "1","2","3","4": 2 1 1 2 3 1 2 1 1 1 ...
 $ Occupation                       : Factor w/ 4 levels "1","2","3","4": 3 2 3 3 3 4 3 2 3 2 ...
 $ No.of.dependents                 : Factor w/ 2 levels "1","2": 1 1 1 1 2 2 1 1 1 1 ...
 $ Telephone                        : Factor w/ 2 levels "1","2": 2 1 1 1 2 2 1 1 1 1 ...
 $ Foreign.Worker                   : Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ...

You can see Credit.Amount variable. In raw data, It has only positive value. But after using ROSE function, It had negative value.

Please help me.... is it right ? ?? ? ?

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  • $\begingroup$ "E" stands for technique? $\endgroup$ – Glen_b Jul 21 '17 at 5:50
  • $\begingroup$ @Glen_b that's not important thing. Any way ROSE means random over sampling examples $\endgroup$ – 이순우 Jul 21 '17 at 6:01

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