Build a Logistic model inside the this file (it's a .py file that has the instructions below). Don't forget to use WOE file to check for IV and WOE. #load the data from the dataset #drop obviously correlated values #reduce Marial Status to four categories -- Married, Separated, Never Married, Widowed #map countries to born in United States or not #determine if any fields are correlated with each other #find statistically significant or unreasonable variables using WOE file #dummy encode all of the non-quantitative values #drop dummyfied variables #create table with base quantitative values and with dummy values #separate for resutls and input sets #split between sets #run logistic regresstion #print classification report #print resuls using printOutCoefficients method to excel and run 5 different rows through the model in excel 

The data set is "adultincome.proc.csv". I'm posting the first 10 lines below to show the format and data included!

age,type-of-employment,hours-worked,occupation,Degree,Years of education,Martial-status,Race,Sex,Native Country,income-80k+ 39,Government,40,Admins, Bachelors,16, Never-married, White, Male, United-States,0 50,Self-Employed,19,Professionals, Bachelors,16, Married-civ-spouse, White, Male, United-States,0 38,Private,40,Service, HS-grad,12, Divorced, White, Male, United-States,0 53,Private,40,Service, 11th,10, Married-civ-spouse, Black, Male, United-States,0 28,Private,40,Professionals, Bachelors,16, Married-civ-spouse, Black, Female, Cuba,0 37,Private,40,Professionals, Masters,17, Married-civ-spouse, White, Female, United-States,0 49,Private,19,Service, 9th,8, Married-spouse-absent, Black, Female, Jamaica,0 52,Self-Employed,40,Professionals, HS-grad,12, Married-civ-spouse, White, Male, United-States