cs263_final_project

Unsupervised training

Modify which plots to show and which steps to compute in unsupervised.py. Then run:

python unsupervised.py

Supervised training: see instructions in supervised.py

Description of most important files:

unsupervised.py: pipeline for unsupervised attack supervised.py: supervised training using logistic regression, SVM, naive bayes mlalgs.py: the bulk of the machine learning algorithms we implemented langmodel.py: English specific computations features.py: cepstrum and FFT feature computation