Rapid-deployment valves probability predictions

Random Forest survival Predictions

Random Forests (RFs) are composed of multiple independent decision trees that are trained independently on a random subset of data. The method was introduced by Breiman et al in 2001, that can take into account censoring. The RSF models was developped by Ishwaran et al. in 2008.

The RF Failire probabilities according to days, may be calculated defining in the right side panel the specific levels of predictors.

Computations have been performed using the randomForestSRC[1] package in R[2] (version 3.6.2).

References

Ishwaran, H., Kogalur, U. B., Blackstone, E. H., & Lauer, M. S. (2008). Random survival forests. The annals of applied statistics, 2(3), 841-860.

2. Team, R. C. (2015). R Foundation for Statistical Computing; Vienna, Austria: 2014. R: A language and environment for statistical computing, 2013.