Feature Normalization Effect in Emotion Classification based on EEG Signals

Orhan AKBULUT

doi:https://doi.org/10.16984/saufenbilder.617642

Makale detayları

Feature Normalization Effect in Emotion Classification based on EEG Signals

Yazarlar:

Orhan AKBULUT

Ana Başlıklar:

Veri işleme & bilgisayar bilimi

Dergi:

Sakarya University Journal of Science 2020 Vol.24 Issue 1, pp.60-66

Belge Tipi:

Makale

Yayın Tarihi:

1/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000556886

DOI:

https://doi.org/10.16984/saufenbilder.617642

Özet:

 


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.


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Makale detayları

Feature Normalization Effect in Emotion Classification based on EEG Signals

Yazarlar: Orhan AKBULUT

Ana Başlıklar: Veri işleme & bilgisayar bilimi

Dergi: Sakarya University Journal of Science 2020 Vol.24 Issue 1, pp.60-66

Belge Tipi: Makale

Yayın Tarihi: 1/2020

Belge Dili: İngilizce

Document ID (Org No.): 2000556886

DOI: https://doi.org/10.16984/saufenbilder.617642

Sayı

Yazarlar:

Orhan AKBULUT

Ana Başlıklar:

Veri işleme & bilgisayar bilimi

Dergi:

Sakarya University Journal of Science 2020 Vol.24 Issue 1, pp.60-66

Belge Tipi:

Makale

Yayın Tarihi:

1/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000556886

DOI:

https://doi.org/10.16984/saufenbilder.617642