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Electricity load forecasting

This example is adapted from https://github.com/probabl-ai/forecasting.

The goal is to have a dataset and prediction pipeline that can be used to experiment with features of skore and other packages.

Contents

For simplicity, historical data is stored in the repo in datasets. Outputs can be stored in results (ignored by git). electricity_load_forecasting.py contains functions for loading data, defining the pipeline, cross-validation splits etc. . eda.py, cross_validate.py and search.py are scripts that perform basic exploratory data analysis, cross-validating the default pipeline, running hyperparameter search & scoring the best model on a held-out set.

requirements.txt lists a few packages used in the scripts.

The current version of the pipeline looks like this:

See the report for an actual run here

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example project to experiment with skore, based on the electricity load forecasting probabl masterclass

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