Feature selection of post-graduation income of college students in the United States

Ewan Thomas Mansell WRIGHT, Qiang HAO, Khaled RASHEED, Yan LIU

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

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 languageEnglish
Title of host publicationSocial, cultural, and behavioral modeling: 11th International Conference, SBP-BRiMS 2018, Washington, DC, USA, July 10-13, 2018, proceedings
EditorsRobert THOMSON, Christopher DANCY, Ayaz HYDER, Halil BISGIN
Place of PublicationCham
PublisherSpringer
Pages38-45
ISBN (Electronic)9783319933726
ISBN (Print)9783319933719
DOIs
Publication statusPublished - 2018

Fingerprint

graduate
income
financial aid
student
data analysis
education
time

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