ctdGAN

Name	ctdGAN JSON
Version	0.1.9 JSON
	download
home_page	https://github.com/lakritidis/ctdGAN
Summary	A Generative Adversarial Network for synthesizing artificial tabular data.
upload_time	2024-12-26 13:58:22
maintainer	Leonidas Akritidis
docs_url	None
author	Leonidas Akritidis
requires_python	None
license	Apache
keywords	ctdgan gan generative adversarial network imbalanced data tabular data deep learning
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            <p>ctdGAN is a Conditional Generative Adversarial Network for alleviating class imbalance in tabular datasets. The model is based on an initial space partitioning step that assigns cluster labels to the input samples. These labels are used to synthesize samples via a probabilistic sampling mechanism. ctdGAN optimizes a loss function that is sensitive to both cluster and class mis-predictions, rendering the modelcapable of generating samples in subspaces that resemble those of the original data distribution.</p><p><b>Licence:</b> Apache License, 2.0 (Apache-2.0)</p><p><b>Dependencies:</b>NumPy, pandas, Matplotlib, seaborn, joblib, Reversible Data Transforms(RDT), scikit-learn, pytorch, Synthetic Data Vault</p><p><b>GitHub repository:</b> <a href="https://github.com/lakritidis/ctdGAN">https://github.com/lakritidis/ctdGAN</a></p>

            

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