Abstract
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. We discuss how higher numbers of students in a cohort who grew up in Zip code areas where over 25% of the population hold a Professional Degree was predictive of more college graduates being classified as High income. Copyright © 2018 Springer International Publishing AG, part of Springer Nature.
| Original language | English |
|---|---|
| Title of host publication | Social, cultural, and behavioral modeling: 11th International Conference, SBP-BRiMS 2018, Washington, DC, USA, July 10-13, 2018, proceedings |
| Editors | Robert THOMSON, Christopher DANCY, Ayaz HYDER, Halil BISGIN |
| Place of Publication | Cham |
| Publisher | Springer |
| Pages | 38-45 |
| ISBN (Electronic) | 9783319933726 |
| ISBN (Print) | 9783319933719 |
| DOIs | |
| Publication status | Published - 2018 |
Citation
Wright, E., Hao, Q., Rasheed, K., & Liu, Y. (2018). Feature selection of post-graduation income of college students in the United States. In R. Thomson, C. Dancy, A. Hyder, & H. Bisgin (Eds.), Social, cultural, and behavioral modeling: 11th International Conference, SBP-BRiMS 2018, Washington, DC, USA, July 10-13, 2018, proceedings (pp. 38-45). Cham: Springer.Keywords
- Attribute selection
- Feature selection
- Post-graduation income classification
- Post-graduation income prediction
- Social stratification