Some variation of COBRA in sequential learning setup

Aryan Bhambu; Arabin Kumar Dey

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arXiv · 2405.04539

Some variation of COBRA in sequential learning setup

Aryan Bhambu·Arabin Kumar Dey

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Abstract

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.

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stat.ML cs.CE cs.LG eess.SP q-fin.CP

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Aryan Bhambu, Arabin Kumar Dey. 2024-04-07. Some variation of COBRA in sequential learning setup. https://arxiv.org/abs/2405.04539

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