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Classifieur - Amin - SVN.ipynb
Classifieur - Marc - Butterworth + k-nn.ipynb
Classifieur-Vincent-MFCC+NaifBayes.ipynb
Classifieurs - Amin - arbre de décision .ipynb
Classifieurs - Thomas - CNN (binaire, 98%).ipynb
Classifieurs - Thomas - Tests Fourier + PCA pour classification binaire i vs j pour tout i et j.ipynb
Classifieurs - Thomas - Tests Fourier + PCA.ipynb
Classifieurs - Thomas - Tests std dev + sklearn.ipynb
Classifieurs_René_FFT_PCA_GPC_KNN.ipynb
Dataset exploration - Grasp and lift.ipynb
Dataset exploration.ipynb
Présentation_nov_2015.pdf
README.md
UltimateFeatureVectorClassifierFromHell.ipynb

README.md

Giving sense to EEG records

As a project during the course IFT6390 "machine learning" by Pascal Vincent from MILA, we have been working on the dataset Mind big data provided by David Vivancos. This repository groups several tests and documents we produced during our work.

Mind big data

[http://www.mindbigdata.com/]

We have focused our work on Mind big data. This dataset, provided by David Vivancos, is composed of records of 2 seconds of EEG signals using several non-medical grade headsets. During the experiment, the subject was presented digits (0 - 9) on a computer, and tried to focus on the digit. We aim at discovering if we can predict which digit was presented using the sensors series.

Usage

If you wish to reproduce our experiments, you can load the ipython notebooks and run the code.

You will require several libraries: numpy and sklearn for most notebooks and Theano for CNN related notebooks.

Team members

  • Amin Shahab
  • Marc Sayn-Urpar
  • René Doumbouya
  • Thomas George
  • Vincent Antaki