KasperGroesLudvigsen/xgboost_time_series
How to use XGBoost for multi-step time series forecasting
This project helps data scientists and machine learning engineers create multi-step time series forecasts using XGBoost. You input historical time series data, and it outputs predictions for future values across a defined forecast horizon. It's designed for practitioners who need to predict several steps ahead in their time series.
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Use this if you need to forecast multiple future time steps for a single time series using a robust, tree-based model like XGBoost.
Not ideal if you require a simple, single-step forecast or prefer deep learning models for your time series prediction tasks.
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Nov 02, 2022
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