ListarModelización, Optimización e Inferencia Estadística (MODES) por tema "Clustering"
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CABRA: Clustering algorithm based on regular arrangement
(Elsevier, 2024)[Abstract]: Clustering is an unsupervised learning technique for organizing complex datasets into coherent groups. A novel clustering algorithm is presented, with a simple grouping concept depending on only one hyperparameter, ... -
Machine learning for multivariate time series with the R package mlmts
(Elsevier B.V., 2023-06)[Abstract]: Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with univariate time series, multivariate time series have typically received much less attention. However, the ... -
Quantile Cross-Spectral Density: A Novel and Effective Tool for Clustering Multivariate Time Series
(Elsevier, 2021)[Abstract] Clustering of multivariate time series is a central problem in data mining with applications in many fields. Frequently, the clustering target is to identify groups of series generated by the same multivariate ... -
Quantile-Based Fuzzy Clustering of Multivariate Time Series in the Frequency Domain
(Elsevier, 2022)[Abstract] A novel procedure to perform fuzzy clustering of multivariate time series generated from different dependence models is proposed. Different amounts of dissimilarity between the generating models or changes on ...