R: Machine Learning Feature Selection for High Dimensional Survival Data

# Machine Learning Feature Selection for High Dimensional Survival Data

## Documentation for package ‘highMLR’ version 1.0.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

coef.highmlr_fit | Coefficients from a highmlr_fit
highmlr | Machine learning feature selection for high dimensional survival data
highmlr_causal | Causal survival forest for heterogeneous treatment effects (experimental)
highmlr_compare | Compare multiple highMLR methods on the same data
highmlr_conformal | Conformal prediction intervals for survival times
highmlr_explain | Time-dependent SHAP explanations for a highmlr_fit (SurvSHAP(t))
highmlr_report | Generate a Quarto/Rmd report skeleton for a highmlr_fit
highmlr_screen | Pre-screen features when p is very large
highmlr_stability | Post-hoc stability analysis of a fitted highmlr_fit
hnscc | High dimensional head and neck cancer survival and gene expression data
plot.highmlr_causal | Causal survival forest for heterogeneous treatment effects (experimental)
plot.highmlr_conformal | Plot method for highmlr_conformal objects
plot.highmlr_explain | Time-dependent SHAP explanations for a highmlr_fit (SurvSHAP(t))
plot.highmlr_fit | Forest / importance plot for a highmlr_fit
predict.highmlr_fit | Predict from a highmlr_fit
print.highmlr_causal | Causal survival forest for heterogeneous treatment effects (experimental)
print.highmlr_conformal | Print method for highmlr_conformal objects
print.highmlr_explain | Time-dependent SHAP explanations for a highmlr_fit (SurvSHAP(t))
print.highmlr_fit | Print method for highmlr_fit
srdata | High dimensional protein gene expression survival data
summary.highmlr_fit | Summary method for highmlr_fit