Koksal, Mehmet YigitÇakar, TunaDemircioğlu, Esin TunaGirisken, Yener2022-11-092022-11-092022Köksal, M. Y., Çakar, T., Tuna, E., & Girişken, Y. (15-18 May 2022). Liking Prediction Using fNIRS and Machine Learning: Comparison of Feature Extraction Methods. In 2022 30th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE. https://doi.org/10.1109/SIU55565.2022.986488797816654509282165-0608https://hdl.handle.net/20.500.11779/1882https://doi.org/10.1109/SIU55565.2022.9864887The fMRI method, which is generally used to detect behavioral patterns, draws attention with its expensive and impractical features. On the other hand, near infrared spectroscopy (fNIRS) method is less expensive and portable, but it is as effective as fMRI in creating a good prediction model. With this method, a model has been developed that can predict whether people like a stimulus or not, using machine learning various algorithms. A comparison was made between feature extraction methods, which was the main focus while developing the model.trinfo:eu-repo/semantics/closedAccessMachine LearningDecision-MakingOptical Brain ImagingfNIRSFeature ExtractionConference Object10.1109/SIU55565.2022.98648872-s2.0-85138706426