BOFRF: A Novel Boosting-Based Federated Random Forest Algorithm on Horizontally Partitioned Data

BOFRF: A Novel Boosting-Based Federated Random Forest Algorithm on Horizontally Partitioned Data

The application of federated learning on ensemble methods is a common practice with the goal of increasing the predictive power of local models. However, although existing federated solutions utilizing ensemble methods can achieve this when the datasets of sites are balanced and of good quality, i.e...

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Bibliographic Details
Main Authors: Mert Gencturk, A. Anil Sinaci, Nihan Kesim Cicekli
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Ensemble learning
federated learning
machine learning
privacy-preservation
random forest classification
Online Access:https://ieeexplore.ieee.org/document/9867984/

Internet

https://ieeexplore.ieee.org/document/9867984/

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