How to impute the missing data with the most frequent value
I have a dataset containing categorical and numerical data and I would like to know how I can impute the missing data with the frequent value.
For example
ID Feature1 Feature 2 Feature 3
_______________________________________
123 core i7 Windows 33844690
334 IOS phone 99983648
Note that the missing values are huge but I can't drop the column.
Is there an operator I can use for nominal data to be replaced with the mode? and the numerical data with average or max?
For example
ID Feature1 Feature 2 Feature 3
_______________________________________
123 core i7 Windows 33844690
334 IOS phone 99983648
Note that the missing values are huge but I can't drop the column.
Is there an operator I can use for nominal data to be replaced with the mode? and the numerical data with average or max?
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Altair EmployeeHi,
you can use Replace Missing Values. Average actually takes the mode for nominal columns.
Cheers,
Martin
Sort by:
1 - 1 of
11
Altair EmployeeHi,
you can use Replace Missing Values. Average actually takes the mode for nominal columns.
Cheers,
Martin