Fuzzy forests for feature selection in high-dimensional survey data: an application to the 2020 US presidential election

Key Points

• The aim is to explore fuzzy forests for selecting important features in high-dimensional survey data related to the 2020 presidential election.
• Utilized a fuzzy forests algorithm for feature selection.
• Applied the methodology to survey data from the 2020 US presidential election.
• Analyzed the significance of various features influencing voter behavior.
• Identified critical features that significantly impact election outcomes.
• Demonstrated the effectiveness of fuzzy forests in high-dimensional settings.