Focal Interest
Focal Interest

Feature selection

  1. Pre-course aptitude tests predicted introductory programming performance
    Study develops pre-course aptitude test to predict introductory programming performance and identify students needing additional support using machine learning models.
  2. Deep learning classified GPA using family and psychological factors
    Deep learning framework classifies undergraduate GPA by integrating family background and psychological factors, achieving 0.798 accuracy in identifying academic risk among Chinese college students.
  3. Quantitative Analysis of Polyphenols in Lonicera caerulea Based on Mid-Infrared Spectroscopy and Hybrid Variable Selection
    Mid-infrared spectroscopy with hybrid variable selection for quantitative polyphenol analysis in Lonicera caerulea, achieving 92% predictive accuracy in high-dimensional small-sample modeling.