Classification of an Individual into High Income or Low Income group based on certain metrics
Attribute Information: 1.age: continuous variable 2. working_sector: sector under which the employee is working 3. financial_weight: weighted attribute to balance the difference in the monetary and working conditions. It is a continuous variable 4. qualification: Eduacational qualification 5. years_of_education: number of years of education; continuous variable 6. tax paid: amount of tax paid by the peron(continuous variable) 7. loan taken: it is a two level categorical variable defining whether the person has taken loan or no 8. marital status: categorical variable 9. occupation : area of work, a categorical variable with 14 levels 10. relationship : provides relationship status of the employee 11. ethnicity : social background (categorical variable ) 12. gender: two level categorical variable 13. gain : it illustrates the financial gain of an person, it is a continuous variable 14. loss: financial loss of the person , it is a continuous variable 15. working_hours : it is a continuous variables describing hours of work of an employee in a week 16. country: describes the origin country of an employee 17. target: Based on the given data your model will have to classify a person into high income / low income.
The approcahes taken are :
- Logistic regression
- Logistic Regression with Step AIC and VIF to regularise and also remove collinearity.
- Logistic Rgeression with Ridge and Lasso regularisation.