Work

Dual-Metric Clustering for Multivariate Time Series: KMeans with DTW and QuadTree with Entropy

Year: 2024

Type: conference-paper

Abstract: The efficacy of machine learning models are contingent on input data quality and model selection itself. In this work we highlight the importance of data quality, particularly in identifying regions within the input space that exhibit similar behavior. Clustering is used to group similar data, and is explored for their potential to enhance model performance by identifying these regions. The aim of this paper is to provide insights into the effectiveness of using clustering to improve machine learning model performance.

DOI: 10.5753/sbbd.2024.243131

Authors: Samuel R. Torres, Raphael Saldanha, Rocío Zorrilla, Vitor Ribeiro, Eduardo H. M. Pena, Fábio Porto

Institutions: Laboratório Nacional de Computação Científica, Institut national de recherche en sciences et technologies du numérique, Universidade Tecnológica Federal do Paraná

Language: English

Topic: Time Series Analysis and Forecasting

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Petrobras

OpenAlex ID: W4403824307

FWCI:

Cites: 9

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Related to: 10