Area-norm COBRA on Conditional Survival Prediction
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Abstract (arXiv)
The paper explores a different variation of combined regression strategy to calculate the conditional survival function. We use regression based weak learners to create the proposed ensemble technique. The proposed combined regression strategy uses proximity measure as area between two survival curves. The proposed model shows a construction which ensures that it performs better than the Random Survival Forest. The paper discusses a novel technique to select the most important variable in the combined regression setup. We perform a simulation study to show that our proposition for finding relevance of the variables works quite well. We also use three real-life datasets to illustrate the model.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 10 of its 38 references that are in the map. First posted on arXiv 1 Sep 2023.
Builds on
10 of 38 references.
References · 10
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- 2022SurvSHAP(t): Time-dependent explanations of machine learning survival modelscited by 24
- 2019Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Ratescited by 8
- 2020A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov boundscited by 7
- 2020SurvLIME-Inf: A simplified modification of SurvLIME for explanation of machine learning survival modelscited by 7
- 2022Concordance based Survival Cobra with regression type weak learnerscited by 2
- 2022Integrated Brier Score based Survival Cobra -- A regression based approachcited by 1
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Citing papers per year: 2026: 1.
1 paper.