Copula-based conformal prediction for Multi-Target Regression
There are relatively few works dealing with conformal prediction for multi-task learning issues, and this is particularly true for multi-target regression. This paper focuses on the problem of providing valid (i.e., frequency calibrated) multi-variate predictions. To do so, we propose to use copula functions applied to deep neural networks for inductive conformal prediction. We show that the proposed method ensures efficiency and validity for multi-target regression problems on various data sets.
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Conformal PredictionMulti-target regressionMulti-Task LearningPredictionregressionvalidSimilar Papers 제목 키워드 기반
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