Browsing by Author "Abdessalem, Talel"
Now showing items 1-3 of 3
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Adaptive random forests for evolving data stream classification
(Springer, 2017)Random forests is currently one of the most used machine learning algorithms in the non-streaming (batch) setting. This preference is attributable to its high learning performance and low demands with respect to input ... -
Adaptive XGBoost for evolving data streams
(IEEE, 2020)Boosting is an ensemble method that combines base models in a sequential manner to achieve high predictive accuracy. A popular learning algorithm based on this ensemble method is eXtreme Gradient Boosting (XGB). We present ... -
River: Machine learning for streaming data in Python
(2021)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, performance metrics and evaluators for different ...
