https://github.com/jzaragosa06/univariate_ts_forecast

Using Large Language Model (Gemini-Pro) to Provide Context-Specific Explanation to Time Series Forecast
https://github.com/jzaragosa06/univariate_ts_forecast

flask timeseries-forecasting xgboost

Last synced: about 1 month ago
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Using Large Language Model (Gemini-Pro) to Provide Context-Specific Explanation to Time Series Forecast

• Host: GitHub
• URL: https://github.com/jzaragosa06/univariate_ts_forecast
• Owner: jzaragosa06
• Created: 2024-08-19T12:36:42.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-08-28T05:00:41.000Z (4 months ago)
• Last Synced: 2024-08-28T06:21:46.614Z (4 months ago)
• Topics: flask, timeseries-forecasting, xgboost
• Language: HTML
• Homepage:
• Size: 19.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Automated Univariate Time Series Forecasting

This project focuses on integrating a large language model (LLM) to offer context-specific explanations for forecasts generated by XGBRegressor. Users input context-specific data, enabling the LLM to provide understandable detailed explanations.