Skip to content

machine learning models for predicting depression based on EEG data

Notifications You must be signed in to change notification settings

maryjis/eeg_depression

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

23 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

eeg_depression

The repository contains machine learning models for classification of Major Depression Disorder patients from healthy controls.

The repository provides two approaches: a standard feature-extracted approach and a deep learning approach. Feature extraction and preparing data were made with https://github.com/ledovsky/eeg-research

Deep learning approach includes 3 notebooks with such models:

  • 3D Autoencoder on spectrum EEG data
  • 2D Autoencoder on spectrum EEG data
  • 2D CNN model

Standard feature-extracted approach includes notebook with training different ml models ( Random Forest, Logistic Regression, KNN, Gradient Boosting etc.) , notebook with extracting important features recieved on the best model and notebook with attemt to use transfer learning from one eeg dataset to another

About

machine learning models for predicting depression based on EEG data

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published