Random Survival Forests (RSFs) are an extension of the traditional random forest algorithm, tailored specifically for analyzing time-to-event data, commonly referred to as survival data. Unlike traditional random forests that deal with classification or regression problems, RSFs are used to predict the time until an event of interest occurs, such as death or disease recurrence in cancer patients.
