2 papers
cs.LG2026
MIHT: A Hoeffding Tree for Time Series Classification using Multiple Instance Learning
Aurora Esteban, Amelia Zafra, Sebastián Ventura
Due to the prevalence of temporal data and its inherent dependencies in many real-world problems, time series classification is of paramount importance in various domains. However,…
cs.LG2024
Hoeffding adaptive trees for multi-label classification on data streams
Aurora Esteban, Alberto Cano, Amelia Zafra +1
Data stream learning is a very relevant paradigm because of the increasing real-world scenarios generating data at high velocities and in unbounded sequences. Stream learning aims…