Name: Random forests with survival data
Start: 2017-08-16T12:30:00+01:00
End: 2017-08-16T13:30:00+01:00
Location: Western Gateway Building, UCC, Room 402

We often want to model the time it takes for some event to occur (e.g. death, failure, etc). In medical research, we typically do this using the Cox proportional hazards model, or some flavor of parametric survival model. Linear models like these are especially useful because model parameters can often be meaningfully interpreted. However, when we are primarily concerned with prediction of future events, the performance of linear models is often outclassed by other algorithms, such as Random Forests, an ensemble method for regression/classification trees. In this meet-up we will demonstrate the use of random survival forests using the R package randomForestSRC. https://cran.r-project.org/web/packages/randomForestSRC/randomForestSRC.pdf

Darren Dahly

Cork (Ireland) R-Users Group

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Statistical Computing

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Predictive Analytics

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R Project for Statistical Computing

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Applied Statistics

Statistical Science

Biostatistics

Statistical Modeling

Random forests with survival data

Western Gateway Building, UCC, Room 402

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Random forests with survival data

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