High-performance exclusion of schizophrenia using a novel machine learning method on EEG data

Using the Random Forest method, we developed a fast-high-performance classification model, which can exclude a potential schizophrenic disorder in a diagnosis of potentially exposed people. Our model mainly consists of three preprocessing steps: ICA, Spectral Analysis using Buettner et al.'s 99-frequency-band-method and normalization. Using this preprocessing pipeline followed by a Random Forest, validated with different parameters, random...