Gender : Gender Value M=Male, F=Female, X=Indeterminate/Intersex/Unspecified
Postal Postcode : Numeric Code
Residential postcode : 1 = Major Cities, 2 = Inner Regional,3 = Outer Regional, 4 = Remote and 5 = Very Remote Socio-Economic: *0-99 where 0 is low Socio-Economic and 99 is high *
School Code : Numeric Code
Educational attainment of first parent : Numeric
Educational attainment of second parent : Numeric
Grade : Numeric between 0 and 100
I would like to training on 2017 data to predict student's grade in 2018 (for example, if we have a student got grade 80 and in 2018 we have a student with the same variables or very similar so the predicted grade should something close to 80)
What have you tried so far? what is your specific problem?
Could you please turn this into a self-contained REPRoducible EXample (reprex)? A reprex makes it much easier for others to understand your issue and figure out how to help.
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