Comparing Methods of Feature Extraction of Brain Activities for Octave Illusion Classification Using Machine Learning

Comparing Methods of Feature Extraction of Brain Activities for Octave Illusion Classification Using Machine Learning

The aim of this study was to find an efficient method to determine features that characterize octave illusion data. Specifically, this study compared the efficiency of several automatic feature selection methods for automatic feature extraction of the auditory steady-state responses (ASSR) data in b...

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Bibliographic Details
Main Authors: Nina Pilyugina, Akihiko Tsukahara, Keita Tanaka
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Sensors
Subjects:
feature selection
machine learning
octave illusion
auditory illusion
MEG
Online Access:https://www.mdpi.com/1424-8220/21/19/6407

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