A Federated Learning Benchmark on Tabular Data: Comparing Tree-Based Models and Neural Networks

arXiv:2405.02074v1 Announce Type: new
Abstract: Federated Learning (FL) has lately gained traction as it addresses how machine learning models train on distributed datasets. FL was designed for parametric models, namely Deep Neural Networks (DNNs).Thus, it has shown promise on image and text tasks. However, FL for tabular data has received little attention. Tree-Based Models (TBMs) have been considered to perform better on tabular data and they are starting to see FL integrations. In this study, we benchmark federated TBMs and …

abstract arxiv benchmark cs.lg data datasets distributed federated learning however image machine machine learning machine learning models networks neural networks parametric tabular tabular data tasks text train tree type