3 papers
cs.DS2026
Online K-d tree for approximate neighborhood search in data streams
Eduardo V. L. Barboza, Robert Sabourin, Rafael M. O. Cruz
The k-Nearest Neighbors (kNN) algorithm has long been widely used in Machine Learning (ML) applications. However, the main concern when using it is the computational cost required…
cs.LG2026
CaDrift: A Time-dependent Causal Generator of Drifting Data Streams
Eduardo V. L. Barboza, Jean Paul Barddal, Robert Sabourin +1
This work presents Causal Drift Generator (CaDrift), a time-dependent synthetic data generator framework based on Structural Causal Models (SCMs). The framework produces a virtuall…
cs.LG2025
IncA-DES: An incremental and adaptive dynamic ensemble selection approach using online K-d tree neighborhood search for data streams with concept drift
Eduardo V. L. Barboza, Paulo R. Lisboa de Almeida, Alceu de Souza Britto +2
Data streams pose challenges not usually encountered in batch-based ML. One of them is concept drift, which is characterized by the change in data distribution over time. Among man…