Comments (2)
Hello,
Yes, the performance of the models can be improved by tuning their hyperparameters with each dataset. But in our work, we executed all models as benchmarks and thus, we executed all of them with their default parameters. We have mentioned that in our paper as well.
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Thanks @rakshitha123 for your response.
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Related Issues (9)
- Unable to reproduce the results from paper HOT 8
- Data leakage for global univariate setting? HOT 2
- UnicodeDecodeError in data_loader.py when reading m4_monthly_dataset.tsf on Windows HOT 1
- License HOT 1
- Missing documentation in the notebook HOT 2
- Why is arima giving an error when I use a subset of NN5 dataset without missing values? HOT 2
- sktime integration of `data_loader.convert_tsf_to_dataframe` HOT 5
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