Fits a stochastic gradient boosting model using the Cox Partial Likelihood distribution.
Supports random search for hyperparameter optimization.
Usage
gbm_pro(X, y_surv, tune = FALSE, cv.folds = 5, max_tune_iter = 10)
Arguments
- X
A data frame of predictors.
- y_surv
A Surv object.
- tune
Logical. If TRUE, performs random search.
- cv.folds
Integer. Number of cross-validation folds.
- max_tune_iter
Integer. Maximum iterations for random search.
Value
An object of class survival_gbm and pro_model.