archettialberto/federated_survival_forests
Federated Learning with Random Survival Forests.
This project helps data scientists and machine learning researchers evaluate a new method for survival analysis, particularly when data is spread across different organizations. It takes in structured patient or customer data (with event times and outcomes) from multiple sources and produces performance metrics for a federated survival model. Researchers working with privacy-sensitive medical, financial, or behavioral data would use this.
No commits in the last 6 months.
Use this if you are a machine learning researcher or data scientist evaluating the performance of a federated survival analysis model on decentralized datasets.
Not ideal if you are looking for a ready-to-deploy predictive tool for survival outcomes in a production environment without doing further research.
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8
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Language
Python
License
MIT
Category
Last pushed
Jan 26, 2024
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