Concordance based Survival Cobra with regression type weak learners

Rahul Goswami; Arabin Kumar Dey

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arXiv · 2209.11919

Concordance based Survival Cobra with regression type weak learners

Rahul Goswami·Arabin Kumar Dey

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Abstract

In this paper, we predict conditional survival functions through a combined regression strategy. We take weak learners as different random survival trees. We propose to maximize concordance in the right-censored set up to find the optimal parameters. We explore two approaches, a usual survival cobra and a novel weighted predictor based on the concordance index. Our proposed formulations use two different norms, say, Max-norm and Frobenius norm, to find a proximity set of predictions from query points in the test dataset. We illustrate our algorithms through three different real-life dataset implementations.

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BibTeX RIS

Rahul Goswami, Arabin Kumar Dey. 2022-09-24. Concordance based Survival Cobra with regression type weak learners. https://arxiv.org/abs/2209.11919

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