Some variation of COBRA in sequential learning setup
<|reference_start|>Some variation of COBRA in sequential learning setup: This research paper introduces innovative approaches for multivariate time series forecasting based on different variations of the combined regression strategy. We use specific data preprocessing techniques which makes a radical change in the behaviour of prediction. We compare the performance of the model based on two types of hyper-parameter tuning Bayesian optimisation (BO) and Usual Grid search. Our proposed methodologies outperform all state-of-the-art comparative models. We illustrate the methodologies through eight time series datasets from three categories: cryptocurrency, stock index, and short-term load forecasting.<|reference_end|>
@article{bhambu2024some,
    title={Some variation of COBRA in sequential learning setup},
    author={Aryan Bhambu, Arabin Kumar Dey},
    journal={arXiv preprint arXiv:2405.04539},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.04539},
    primaryClass={stat.ML cs.CE cs.LG eess.SP q-fin.CP}
}