https://github.com/Olliang/Statistical-Similarity-Measurement
A methodology designed to validate the statistical similarity of synthetic data generated by GAN models. The metrics contain Auto-encoder, PCA, t-SNE, KL-divergence, Clustering, and Cosine Similarity.
https://github.com/Olliang/Statistical-Similarity-Measurement
methodology similarity-measures similarity-metric synthetic-data
Last synced: about 1 month ago
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A methodology designed to validate the statistical similarity of synthetic data generated by GAN models. The metrics contain Auto-encoder, PCA, t-SNE, KL-divergence, Clustering, and Cosine Similarity.
- Host: GitHub
- URL: https://github.com/Olliang/Statistical-Similarity-Measurement
- Owner: Olliang
- Created: 2020-04-01T23:32:36.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2020-06-25T17:18:06.000Z (almost 5 years ago)
- Last Synced: 2024-04-08T02:31:46.424Z (about 1 year ago)
- Topics: methodology, similarity-measures, similarity-metric, synthetic-data
- Language: Jupyter Notebook
- Homepage:
- Size: 2.93 MB
- Stars: 9
- Watchers: 2
- Forks: 0
- Open Issues: 0
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- awesome-data-synthesis - Statistical-Similarity-Measurement - A methodology designed to validate the statistical similarity of synthetic data generated by GAN models. The metrics contain Auto-encoder, PCA, t-SNE, KL-divergence, Clustering, and Cosine Similarity. (Metrics and dataset evaluation / Tabular)