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GitHub / CatSatOK / Prophets-of-Profit-Evaluating-Synthetic-Data-Techniques-in-Financial-Forecasting-Models

An comparative investigation into WGAN-GP, CTGAN, TimeGAN and DoppelGANger usage for generating synthetic time series finance data for use in forecasting model

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CatSatOK%2FProphets-of-Profit-Evaluating-Synthetic-Data-Techniques-in-Financial-Forecasting-Models

Stars: 0
Forks: 0
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 1.71 MB
Dependencies parsed at: Pending

Created at: over 1 year ago
Updated at: about 1 year ago
Pushed at: about 1 year ago
Last synced at: about 1 year ago

Topics: feature-engineering, financial-data, generative-adversarial-network, predictive-modeling, stock-price-prediction, synthetic-data-generation, time-series

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