In this project, we worked on analyzing brain signals using an EEG dataset. Our goal is to determine whether the patient has any chance of being diagnosed with Psychosis. The dataset, taken from Mendeley, contains EEG reports of healthy and First Episode Psychosis individuals. We have conducted preprocessing using MNE Python package. This project utilises Logistic Regression techniques to train the machine learning model. Through Grid Search Cross-Validation, the model produces the best score of 70%.
