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Comparative Machine Learning for Federal Funds Rate Prediction with Sentiment and Leadership Features

  • East Tennessee State University

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publication2025 International Symposium on Networks, Computers and Communications, ISNCC 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665457682
DOIs
StatePublished - 2025
Event2025 International Symposium on Networks, Computers and Communications, ISNCC 2025 - Paris, France
Duration: Oct 27 2025Oct 29 2025

Publication series

Name2025 International Symposium on Networks, Computers and Communications, ISNCC 2025

Conference

Conference2025 International Symposium on Networks, Computers and Communications, ISNCC 2025
Country/TerritoryFrance
CityParis
Period10/27/2510/29/25

ASJC Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

Keywords

  • Artificial Intelligence
  • Consumer Sentiment
  • Economic Forecasting
  • Elastic Net
  • Federal Funds Rate
  • Machine Learning
  • Monetary Policy
  • XGBoost

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