Published May 13, 2024 | Version v1
Conference paper Open

Subset Models for Multivariate Time Series Forecast

Authors/Creators

  • 1. ROR icon Research Centre Inria Sophia Antipolis - Méditerranée
  • 2. ROR icon Laboratório Nacional de Computação Científica
  • 3. ROR icon Fundação Oswaldo Cruz

Description

Abstract: Multivariate time series find extensive applications in conjunction with machine learning methodologies for scenario forecasting across various domains. Nevertheless, certain domains exhibit inherent complexities and diversities, which detrimentally impact the predictive efficacy of global models. This ongoing study introduces a Subset Modeling Framework designed to acknowledge the inherent diversity within a domain’s multivariate space. Comparative assessments between subset models and global models are conducted in terms of performance, revealing compelling findings and suggesting the potential for further exploration and refinement of this novel framework.

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