Counterfactual Explanation of Machine Learning Survival Models

نویسندگان

چکیده

A method for counterfactual explanation of machine learning survival models is proposed. One the difficulties solving problem that classes examples are implicitly defined through outcomes a model in form functions. condition establishes difference between functions original example and introduced. This based on using distance mean times to event. It shown can be reduced standard convex optimization with linear constraints when explained black-box Cox model. For other models, it proposed apply well-known Particle Swarm Optimization algorithm. Numerical experiments real synthetic data demonstrate method.

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ژورنال

عنوان ژورنال: Informatica

سال: 2021

ISSN: ['0350-5596', '1854-3871']

DOI: https://doi.org/10.15388/21-infor468