Emotion Recognition using Gradient Boosting Machine Algorithm
Sujeeth T.1, Y. Srinivas2, Nagesh Vadaparthi3
1Sujeeth T., Asst. Prof., SEAGI and Research Scholar, GIT, GITAM University, Visakhapatnam (Andhra Pradesh), India.
2Y Srinivas, Professor, Department of IT, GIT, GITAM University, Visakhapatnam (Andhra Pradesh), India.
3Nagesh Vadaparthi, Professor, Department of IT, MVGR College of Engineering, Vizianagaram (Andhra Pradesh), India.
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 515-520 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7132068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The technological advancements are helping the medical field by introducing more sophisticated equipment. One such equipment is Electroencephalography (EEG) which helps in reading the brain waves. Brain waves are the reflection of the actual emotions raised in the brain cortex. Various algorithms have been proposed for effectively recognizing the emotions using the EEG data. But, the accuracy has been always a matter of fact which throws a challenge to the researchers. Hence, in this paper we have proposed an effective machine learning techniques Gradient Boosting Algorithm which can classify and predict the emotion more accurately.
Keywords: Electroencephalography, Machine Learning, Gradient Boosting, Brodmann’s.
Scope of the Article: Machine Learning