Integrating Machine Learning and Cognitive Modeling of Decision Making

Implementation of various hybrid models based on MLBA and ML for human choice prediction.

Reproducing the results of my thesis

Run the follwoing R scripts to estimate MLBA using the hierarcical Bayesian method:

The results are already saved in hb_mlba folder.

Run the following to train the models and get their results.

python run.py

After that, run the follwoing to generate the reports and the figures of the thesis saved in the ./out/res/ folder.

python paper_reports.py

Name		Name	Last commit message	Last commit date
Latest commit History 92 Commits
data		data
hb_mlba		hb_mlba
hb_mlba_code		hb_mlba_code
.gitignore		.gitignore
Prepare Criminal Data.ipynb		Prepare Criminal Data.ipynb
Prepare Rectangle Data.ipynb		Prepare Rectangle Data.ipynb
README.md		README.md
build-docker.sh		build-docker.sh
cp.sh		cp.sh
cv.py		cv.py
dockerfile		dockerfile
explore.py		explore.py
helpers.py		helpers.py
lba_dist.py		lba_dist.py
lba_dist_tests.py		lba_dist_tests.py
mlba.py		mlba.py
mlba_nn.py		mlba_nn.py
mlba_nn_m.py		mlba_nn_m.py
mlba_tests.py		mlba_tests.py
mlp.py		mlp.py
paper_reports.py		paper_reports.py
profiling.py		profiling.py
report.py		report.py
report_params.py		report_params.py
requirements.txt		requirements.txt
run-docker.sh		run-docker.sh
run.py		run.py
scaler.py		scaler.py
synthetic.py		synthetic.py