160 citations · 227 across the 9 of their papers we have counts for
3 papers · 1 filter
River: machine learning for streaming data in Python
Jacob Montiel, Max Halford, Saulo Martiello Mastelini +8
River is a machine learning library for dynamic data streams and continual learning. It provides multiple state-of-the-art learning methods, data generators/transformers, performan…
Machine Learning (In) Security: A Stream of Problems
Fabrício Ceschin, Marcus Botacin, Albert Bifet +4
Machine Learning (ML) has been widely applied to cybersecurity and is considered state-of-the-art for solving many of the open issues in that field. However, it is very difficult t…
An Eager Splitting Strategy for Online Decision Trees
Chaitanya Manapragada, Heitor M Gomes, Mahsa Salehi +2
Decision tree ensembles are widely used in practice. In this work, we study in ensemble settings the effectiveness of replacing the split strategy for the state-of-the-art online t…