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.

翻译：本文探讨了一种用于计算条件生存函数的组合回归策略变体。我们采用基于回归的弱学习器构建所提出的集成技术。该组合回归策略利用两条生存曲线之间的面积作为邻近度度量。所提出的模型结构确保其性能优于随机生存森林。本文讨论了在组合回归框架下选择最重要变量的新方法。通过仿真研究，我们验证了所提出的变量相关性判定方法的有效性。此外，我们使用三个真实数据集对所提模型进行了实证分析。