
The proposed Interpretable Client Decision Tree Aggregator For Federated Learning (ICDTA4FL) process aggregates multiple client decision trees into a global interpretable decision tree model, improving performance over local models while maintaining the inherent interpretability of decision trees.


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an-interpretable-client-decision-tree-aggregation-process-for-federated-learning-to-improve-model-performance-and-maintain-interpretability


An Interpretable Client Decision Tree Aggregation Process for Federated Learning to Improve Model Performance and Maintain Interpretability
