Hidden Markov Models (HMM)
Hidden Markov Model code developed from scratch to be used to identify deceptive behavior from the ROC-HCI deception dataset.
Authors: Taylan Sen and Matt Levin
- hmm.py - Implements and test a hidden Markov model
- truth_bluff.py - Dual-HMM classification on a dataset using cross-validation
- lstm_hmm.py - Modified HMM to avoid exponential decay of prolonged hidden states
- runner.sh - Used to deploy code on a BlueHive computing cluster (SLURM system)
- analysis - Jupyter notebooks to analyze results and code to apply confidence-based thresholds to results
- sh - Shell scripts for dispatching jobs to obtain the dataset and other utilities