1 code implementation • 3 Dec 2021 • Vithya Yogarajan, Bernhard Pfahringer, Tony Smith, Jacob Montiel
Improving the tail-end label predictions in multi-label classifications of medical text enables the potential to understand patients better and improve care.
1 code implementation • 1 Oct 2021 • Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer
This study focuses on techniques used for the multi-label classification of medical text.
2 code implementations • 8 Dec 2020 • Jacob Montiel, Max Halford, Saulo Martiello Mastelini, Geoffrey Bolmier, Raphael Sourty, Robin Vaysse, Adil Zouitine, Heitor Murilo Gomes, Jesse Read, Talel Abdessalem, Albert Bifet
It is the result from the merger of the two most popular packages for stream learning in Python: Creme and scikit-multiflow.
1 code implementation • 15 May 2020 • Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet
The proposed method creates new members of the ensemble from mini-batches of data as new data becomes available.
2 code implementations • 29 Mar 2020 • Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer
We also show that high dimensional embeddings pre-trained using health-related data present a significant improvement in a multi-label setting, similarly to the way they improve performance for binary classification.
1 code implementation • 12 Jul 2018 • Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem
Scikit-multiflow is a multi-output/multi-label and stream data mining framework for the Python programming language.