This repository is for the subject "direct research in computer science B" from the university of Tsukuba.
The goal on this project is to produce syntethic data to generate new datasets and balance unbalanced databases. More information can be found on the pdf.
The database credicard is not included on this github because of its size, you can download it on https://www.kaggle.com/mlg-ulb/creditcardfraud/home. If you do, include it in the directory directed_research_CS_2018/original_data/
-classification_random_tree: Evaluate a database using decision tree. The training and test sets can be chosen in the notebook
-compare_original_synthetic: Compare the original and a synthetic dataset by showing visual graphs
-create_fake_data: Uses an already trained model to create fake data
-data_analysis: Show graphics of the original databases
-fake_data_analysis: Compare the original and a synthetic database by graphs
-simple_gan: Create a GAN for the selected database