Year 2020, Volume 24 , Issue 1, Pages 60 - 66 2020-02-01

Feature Normalization Effect in Emotion Classification based on EEG Signals

Orhan AKBULUT [1]


Normalization of data in classification-based problem is a fundamental task where binary or multi classifier systems integrate it as a sub-system.  Normalization can be thought as a mapping function that makes a transformation from one space to another space. Different types of normalization methods are proposed depending on the data content. Recently, researches are carried out on whether this process is really necessary. In this paper, the performances of the different normalization methods for Electroencephalogram (EEG) signal based emotion classification are evaluated. Support vector machine based binary classifier is used in emotion classification. Different kernel functions for support vector machine are also considered. Although the experimental findings may not reveal a significant performance difference between different types of normalization, the normalization process increases classification performance of the emotion recognition, in general.

normalization, classification, support vector machine
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Primary Language en
Subjects Computer Science, Theory And Methods
Published Date February 2020
Journal Section Research Articles
Authors

Orcid: 0000-0003-0096-0688
Author: Orhan AKBULUT (Primary Author)
Institution: Kocaeli University
Country: Turkey


Dates

Application Date : September 9, 2019
Acceptance Date : October 7, 2019
Publication Date : February 1, 2020

Bibtex @research article { saufenbilder617642, journal = {Sakarya University Journal of Science}, issn = {1301-4048}, eissn = {2147-835X}, address = {}, publisher = {Sakarya University}, year = {2020}, volume = {24}, pages = {60 - 66}, doi = {10.16984/saufenbilder.617642}, title = {Feature Normalization Effect in Emotion Classification based on EEG Signals}, key = {cite}, author = {AKBULUT, Orhan} }
APA AKBULUT, O . (2020). Feature Normalization Effect in Emotion Classification based on EEG Signals. Sakarya University Journal of Science , 24 (1) , 60-66 . DOI: 10.16984/saufenbilder.617642
MLA AKBULUT, O . "Feature Normalization Effect in Emotion Classification based on EEG Signals". Sakarya University Journal of Science 24 (2020 ): 60-66 <http://www.saujs.sakarya.edu.tr/en/issue/49430/617642>
Chicago AKBULUT, O . "Feature Normalization Effect in Emotion Classification based on EEG Signals". Sakarya University Journal of Science 24 (2020 ): 60-66
RIS TY - JOUR T1 - Feature Normalization Effect in Emotion Classification based on EEG Signals AU - Orhan AKBULUT Y1 - 2020 PY - 2020 N1 - doi: 10.16984/saufenbilder.617642 DO - 10.16984/saufenbilder.617642 T2 - Sakarya University Journal of Science JF - Journal JO - JOR SP - 60 EP - 66 VL - 24 IS - 1 SN - 1301-4048-2147-835X M3 - doi: 10.16984/saufenbilder.617642 UR - https://doi.org/10.16984/saufenbilder.617642 Y2 - 2019 ER -
EndNote %0 Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi Feature Normalization Effect in Emotion Classification based on EEG Signals %A Orhan AKBULUT %T Feature Normalization Effect in Emotion Classification based on EEG Signals %D 2020 %J Sakarya University Journal of Science %P 1301-4048-2147-835X %V 24 %N 1 %R doi: 10.16984/saufenbilder.617642 %U 10.16984/saufenbilder.617642
ISNAD AKBULUT, Orhan . "Feature Normalization Effect in Emotion Classification based on EEG Signals". Sakarya University Journal of Science 24 / 1 (February 2020): 60-66 . https://doi.org/10.16984/saufenbilder.617642
AMA AKBULUT O . Feature Normalization Effect in Emotion Classification based on EEG Signals. SAUJS. 2020; 24(1): 60-66.
Vancouver AKBULUT O . Feature Normalization Effect in Emotion Classification based on EEG Signals. Sakarya University Journal of Science. 2020; 24(1): 66-60.