/masters_project_2020

UCL Master's Project - Investigating Bayesian Network structure learning methods for the application to Alzheimer's/Schizophrenia Data.

Primary LanguageR

Master's Project (2020)

Submitted thesis: masters_thesis.pdf.

Code DOCUMENTATION INCOMPLETE

The general purposes of the files are as follows:

  • graph_plotting_gaussian.R and graph_plotting_network.R plot figures for the random Gaussian and biological network results, respectively.
  • main_gaussian_xval.R and main_network_xval.R run the main hyperparameter validation experiments on the random Gaussian and biological networks, respectively.
  • generate_simulated_data.py generates data from user-defined or random linear gaussian/gamma Bayesian Networks
  • sachs_script_cont.R and sachs_script_discrete.R run experiments on the RAF Sachs data for continuous and discrete learning algorithms, respectively.
  • sim_gaussian_xval.R and sim_data_pathways.R contain the xvalidation functions called in the random Gaussian and bio network main files, respectively.
  • utils.R contains helper functions used across all files.

TO DOs

  • Implemeant variance update step on NOTEARS
  • ...