Sleep Classification with Python Using EEG, Sklearn and MNE - Part 1

Explore the second part of an EEG sleep stage classification tutorial using Python, Sklearn, and MNE. Learn how to expand the classifier by incorporating data from 10 additional participants, introducing a new class, and implementing Leave-One-Subject-Out cross-validation. Dive into the code implementation, starting with an introduction and project overview before delving into the technical aspects. Gain insights on power spectral density (PSD) through a recommended blog post. Conclude with a summary of the achieved results and compare them to the previous iteration covered in the linked first part of the series.