# Concordance based Survival Cobra with regression type weak learners

arXiv: https://arxiv.org/abs/2209.11919 · HTML: https://mlsanity.com/paper/2209.11919/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 11 references that are in the map.
- First posted on arXiv 24 Sep 2022.

## Builds on (most cited first, 1 of 1)

- [COBRA: A Combined Regression Strategy](https://mlsanity.com/paper/1303.2236/) (2013)

## Built on by (most cited first, 2 of 2)

- [Integrated Brier Score based Survival Cobra -- A regression based approach](https://mlsanity.com/paper/2210.12006/) (2022)
- [Area-norm COBRA on Conditional Survival Prediction](https://mlsanity.com/paper/2309.00417/) (2023)

## Abstract (arXiv)

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.