A weighted random survival forest
This is an incremental improvement for researchers and practitioners in survival analysis, offering enhanced predictive performance in specific applications.
The paper tackles the problem of improving survival prediction accuracy by modifying the random survival forest to use weighted averaging of tree hazard functions, with weights optimized to maximize Harrell's C-index, and demonstrates outperformance over the original random survival forest in real data examples.
A weighted random survival forest is presented in the paper. It can be regarded as a modification of the random forest improving its performance. The main idea underlying the proposed model is to replace the standard procedure of averaging used for estimation of the random survival forest hazard function by weighted avaraging where the weights are assigned to every tree and can be veiwed as training paremeters which are computed in an optimal way by solving a standard quadratic optimization problem maximizing Harrell's C-index. Numerical examples with real data illustrate the outperformance of the proposed model in comparison with the original random survival forest.