EEG-Based Emotion Classification Using Stacking Ensemble Approach
Rapid advancements in the medical field have drawn much attention to automatic emotion classification from EEG data. People’s emotional states are crucial factors in how they behave and interact physiologically. The diagnosis of patients’ mental disorders is one potential medical use. When feeling w...
Main Authors: | Subhajit Chatterjee, Yung-Cheol Byun |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-11-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/21/8550 |
Similar Items
-
Automatic Sleep Stage Classification With Single Channel EEG Signal Based on Two-Layer Stacked Ensemble Model
by: Jinjin Zhou, et al.
Published: (2020-01-01) -
Prediction of Willingness to Pay for Airline Seat Selection Based on Improved Ensemble Learning
by: Zehong Wang, et al.
Published: (2022-01-01) -
A robust and consistent stack generalized ensemble-learning framework for image segmentation
by: Zahra Faska, et al.
Published: (2023-07-01) -
Research on Student Performance Prediction Based on Stacking Fusion Model
by: Fuxing Yu, et al.
Published: (2022-10-01) -
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
by: Much Aziz Muslim, et al.
Published: (2023-05-01)