reviewInternational Journal of Data Science and AnalyticsFeb 3, 2024Closed access

A review of random forest-based feature selection methods for data science education and applications

RIReza IranzadXLXiao Liu

FedEx (United States) · Georgia Institute of Technology

Indexed incrossref

Abstract

No abstract available for this paper.

Citation impact

194
total citations
FWCI
60.80
Percentile
100%
References
38
Citations per year

Authors

2

Topics & keywords

Topics
Keywords
  • Feature selection
  • Random forest
  • Computer science
  • Feature (linguistics)
  • Capstone
  • Selection (genetic algorithm)
  • Software
  • Data science
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
No related works found for this paper.

Funding