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Sos #49
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…diting version of load_forecasting_csv. It can also evaluate this dataset with a new function eval_forecasting_unsupervised. Also includes additional utility functions and configuration
…diting version of load_forecasting_csv. It can also evaluate this dataset with a new function eval_forecasting_unsupervised. Also includes additional utility functions and configuration
…s loader, whilst also generating MSE and MAE (metrics were previously not being calculated correctly becasue of incompatible data reshaping)
…e_retail as well as ts2vec_online_retail_II_data (using load_forecast_csv). However, ts2vec currently trains on restructured_ts2vec_online_retail with Customer ID as a forecasting target feature rather than a covariate (as with datetime embedding features). TS2Vec is able to learn representations better for ts2vec_online_retail_II_data, which only includes Quantity and Price as target features, which is evident as restructured_ts2vec_online_retail have higher MSE and MAE values whilst also starting with a higher training loss value. Perhaps embedding the customer ID instead of feeding it as a forecasting feature will result is better representation learning
… trained with customer embeddings
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