160 citations · 163 across the 4 of their papers we have counts for
4 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…
Adaptive XGBoost for Evolving Data Streams
Jacob Montiel, Rory Mitchell, Eibe Frank +3
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 e…
Scikit-Multiflow: A Multi-output Streaming Framework
Jacob Montiel, Jesse Read, Albert Bifet +1
Scikit-multiflow is a multi-output/multi-label and stream data mining framework for the Python programming language. Conceived to serve as a platform to encourage democratization o…
Dynamic recommender system : using cluster-based biases to improve the accuracy of the predictions
Modou Gueye, Talel Abdessalem, Hubert Naacke
It is today accepted that matrix factorization models allow a high quality of rating prediction in recommender systems. However, a major drawback of matrix factorization is its sta…