Reference

All functions
as_kernels()	Prepare Tuned Kernels for Random Machines
as_kernels(<random_machines_tune>)	Extract Best Kernels from Grid Search Results
as_kernels(<random_machines_tune_optuna>)	Extract Best Kernels from Optuna Results
`$`(<fastsvm_custom_kernel>)	Accessor for Custom Kernel Parameters
coef(<fastsvm>)	Extract sample-wise coefficients (alpha_i) from a fastsvm model
data_generation()	Example data generator for testing FastSurvivalSVM
fastsvm()	Fit FastKernelSurvivalSVM (scikit-survival) from an R data frame
get_params_fastsvm()	Extract hyperparameters of a fastsvm model
grid_kernel()	Create a Kernel Grid or Single Instance (Smart Wrapper)
opt_cat()	Define Categorical Parameter for Optuna Search Space
opt_float()	Define Float Parameter for Optuna Search Space
opt_int()	Define Integer Parameter for Optuna Search Space
predict(<fastsvm>)	Predict risk scores or transformed survival times from a fastsvm model
predict(<random_machines>)	Predict method for Random Machines
print(<fastsvm>)	Print method for fastsvm objects
print(<fastsvm_custom_kernel>)	Print method for custom kernels
print(<fastsvm_grid>)	Print method for single tuning result
print(<random_machines>)	Print method for random_machines
print(<random_machines_tune>)	Print method for Random Machines tuning results
print(<random_machines_tune_optuna>)	Print method for Optuna results
print(<summary.fastsvm>)	Print method for summary.fastsvm objects
random_machines()	Parallel Bagging for FastKernelSurvivalSVM (Random Machines)
score()	Generic function for computing concordance index (score)
score(<fastsvm>)	Concordance index for a fastsvm model
score(<random_machines>)	Score method for Random Machines
summary(<fastsvm>)	Summary method for fastsvm objects
tune_fastsvm()	Single Grid Search for FastKernelSurvivalSVM
tune_fastsvm_optuna()	Tune FastSurvivalSVM using Optuna (Single Kernel Optimization)
tune_random_machines()	Multi-Kernel Tuning for Random Machines
tune_random_machines_optuna()	Multi-Kernel Hyperparameter Tuning via Optuna