Emotion Classification with EEG and Random Forest
Published:Dec 26, 2025 17:20
•1 min read
•ArXiv
Analysis
This paper presents a practical application of EEG technology and machine learning for emotion recognition. The use of a readily available EEG headset (EMOTIV EPOC) and the Random Forest algorithm makes the approach accessible. The high accuracy for happiness (97.21%) is promising, although the performance for sadness and relaxation is lower (76%). The development of a real-time emotion prediction algorithm is a significant contribution, demonstrating the potential for practical applications.
Key Takeaways
Reference
“The Random Forest model achieved 97.21% accuracy for happiness, 76% for relaxation, and 76% for sadness.”