The code in this repository is used in the Bachelor Thesis of Rutger Mauritz
Runpannel
:
- From this file both the performance of the DAE and PIBN model are tested on several synthetic data sets
- The data-sets are loaded from the
\Datasets
directory
DataQuality
:
- This file contains quality measures that are used for evaluation of the model performance
- Those quality measures are a.o. used in
Runpannel
DataPyAgrum
:
- Used for creating synthetic data sets via a Bayesian Network
- Contains an example of how a Bayesian Network can be constructed such that data can be sampled from it
- Used in
Runpannel
DataConversion
:
- Contains two methods:
- dataConversion: is used to add noise to the ground truth data and converts the synthetic data to one-hot encoding like structures
- noise: is used to deliberately add noise to the already corrupted training data. this is a part of the regularization of the DAE
- Used in AE_denoising
BN_sup
:
- Implementation of the supervised PIBN model. It loads a pre-defined Bayesian Network (.bif file) and propagates the probabilistic data as virtual evidence through this BN, after which it extracts the posterior probabilities
AE_denoising
:
- Implementation of the Denoising Autoencoder Model. This trained model is then applied to unseen corrupted test-data after which the resulting output is return, together with the training history
Backend
:
- Contains a method jsd that is a Keras implementation of the Jensen Shannon Divergence
- Used in AE_denoising for training
\Archive
:
- Contains some extra files that are not necessary for the main process anymore.
\Datasets
:
- Contains the data sets that are used in
runpannel
to evaluate the model performances. - Each of these data sets contains a description of its underling Bayesian Network (BN) model and comes with a .csv file containing the data, a .png file for a visualization of the BN network and a .bif file that can be used in PyAgrum.
\Results
:
- A directory for storing the results of model evaluations.
\Images
:
- Contains images that are used in the Bachelor Thesis
- Numpy
- Pandas
- Keras
- PyAgrum: https://agrum.gitlab.io/pages/pyagrum.html
- Sklearn