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：本文探索了一种结合回归策略的不同变体来计算条件生存函数。我们采用基于回归的弱学习器来构建所提出的集成技术。该结合回归策略使用两个生存曲线之间的面积作为邻近性度量。所提出的模型展示了一种结构，确保其性能优于随机生存森林。本文讨论了一种在结合回归框架中选择最重要变量的新颖技术。我们通过模拟研究证明，所提出的变量相关性判定方法效果良好。此外，我们使用三个真实数据集来展示该模型。