Parent project - Training School
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Updated
Mar 21, 2023 - Jupyter Notebook
Parent project - Training School
This repository offers a comprehensive overview of various analytical techniques for fraud detection and provides implementation guidance for an effective fraud prevention solution to help you detect fraud early.
Files for the synthetic data presentation at the Open Science Festival 2022
A Framework for Evaluating Recommender Systems on Synthetic Data Classes
In this repository, I tried to investigate the utility of synthetic data generated by DataSynthesizer and Synthetic Data Vault in machine learning tasks. I applied the Random Forest, Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Naive Bayes algorithms to the synthetic data and made a comparison.
The public repo of experiments from paper "Performance Ranking of Recommender Systems on Simulated Data" by Stavinova et al.
Generates midi notes to join two different midi snippets by interpolation with a cubic spline curve
A python module to generate synthetic images from 3D models, for use in image detection/segmentation tasks.
TNO PET Lab - Synthetic Data Generation (SDG) - Graph - Generation - GraphBin
Implementation for the paper: "Privacy-preserving data release leveraging optimal transport and particle gradient descent"
Synthetic Data Generation and Evaluation
Synthetic Data Generation (SDG) by Gaussian Mixture Model (GMM) Distribution
SYNDATA software includes a suite of statistical/machine learning models to generate discrete/categorical synthetic data.
Synthetic Data Generation by Kernel Density Estimation (KDE)
Synthetic Data Generation by Differential Evolution (DE)
TNO PET Lab - Synthetic Data Generation (SDG) - Tabular - Evaluation - Utility Metrics
Synthetic Data Generation by Markov Chain Monte Carlo (MCMC)
Wasserstein Generative Adversarial Network (WGAN) with Gradient Penalty (GP) for generation of synthetic diseased fingerprints.
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