  This study investigated the most important attributes of the 6-year
post-graduation income of college graduates who used financial aid during their
time at college in the United States. The latest data released by the United
States Department of Education was used. Specifically, 1,429 cohorts of
graduates from three years (2001, 2003, and 2005) were included in the data
analysis. Three attribute selection methods, including filter methods, forward
selection, and Genetic Algorithm, were applied to the attribute selection from
30 relevant attributes. Five groups of machine learning algorithms were applied
to the dataset for classification using the best selected attribute subsets.
Based on our findings, we discuss the role of neighborhood professional degree
attainment, parental income, SAT scores, and family college education in
post-graduation incomes and the implications for social stratification.
