R: Interpretable Survival Machine Learning Framework

# Interpretable Survival Machine Learning Framework

## Documentation for package ‘survalis’ version 0.7.1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

auc_survmat | Time-Dependent AUC from a Survival-Probability Matrix
benchmark_default_survlearners | Benchmark Multiple Survival Learners (Cross-Validation Wrapper)
benchmark_tuned_survlearners | Benchmark Tuned Survival Learners with Nested Cross-Validation
best_survlearner | Select the Best Survival Learner by a Given Metric
brier | Brier Score with IPCW for a Single Time Point
cindex_survmat | Concordance Index from a Survival-Probability Matrix
compute_ale | Accumulated Local Effects (ALE) for Survival Models
compute_calibration | Calibration of Survival Predictions at a Single Time Point
compute_counterfactual | Compute individual counterfactual changes to increase survival
compute_interactions | Compute Feature Interactions for Survival Predictions
compute_pdp | Partial Dependence and ICE for Survival Predictions
compute_shap | Compute local SHAP-like contributions for survival predictions
compute_surrogate | Local Surrogate Explanation for Survival Predictions (LIME-style)
compute_tree_surrogate | Compute Tree-Based Surrogate Model for Survival Predictions
compute_varimp | Permutation variable importance for survival models
cv_plot | Boxplot of Cross-Validation Metric Distributions
cv_summary | Summarize Cross-Validation Results
cv_survlearner | Cross-Validate a Survival Learner (fold-mapped with 'fmapn')
cv_survmetalearner | Cross‑Validate a Stacked Survival Meta‑Learner
ece_survmat | Expected Calibration Error (ECE) at a Single Time Point
fit_aalen | Fit an Additive Hazards (Aalen) Model
fit_aftgee | Fit an Accelerated Failure Time Model Using Generalized Estimating Equations
fit_bart | Fit a Bayesian Additive Regression Trees (BART) Survival Model
fit_blackboost | Fit a Componentwise Gradient Boosted Cox Model (blackboost)
fit_bnnsurv | Fit a kNN–Ensemble Survival Model (bnnSurvival)
fit_cforest | Fit a Conditional Inference Survival Forest
fit_coxph | Fit a Cox Proportional Hazards Model
fit_flexsurvreg | Fit a Parametric Survival Regression Model Using flexsurvreg
fit_glmnet | Fit a Penalized Cox Proportional Hazards Model (glmnet)
fit_orsf | Fit an Oblique Random Survival Forest (ORSF) Model
fit_ranger | Fit a Survival Random Forest Model Using ranger
fit_rpart | Fit a Survival Tree Model using 'rpart'
fit_rsf | Fit a Random Survival Forest (RSF) Model
fit_selectcox | Fit a Predictor-Selection Cox Model (pec::selectCox, mlsurv_model-compatible)
fit_stpm2 | Fit a Flexible Parametric Survival Model (rstpm2, mlsurv_model-compatible)
fit_survdnn | Fit a Deep Neural Network Survival Model (mlsurv_model-compatible)
fit_survmetalearner | Fit a Stacked Survival Meta‑Learner (Time‑Varying NNLS)
fit_survsvm | Fit a Survival SVM Model (mlsurv_model-compatible)
fit_xgboost | Fit an XGBoost Survival Model (mlsurv_model-compatible)
iae_survmat | Integrated Absolute Error Against Kaplan-Meier
ibs_survmat | Integrated Brier Score (Discrete Integration)
ise_survmat | Integrated Squared Error Against Kaplan-Meier
list_interpretability_methods | List interpretability methods available in survalis
list_metrics | List Available Evaluation Metrics
list_survlearners | List survival learners available in survalis
list_tunable_survlearners | List tunable survival learners
plot_ale | Plot ALE Curves for Survival Models
plot_benchmark | Plot Benchmark Distributions Across Learners
plot_calibration | Plot Calibration Curve for Survival Predictions
plot_counterfactual | Plot Counterfactual Recommendations
plot_interactions | Plot Interaction Strengths for Survival Models
plot_pdp | Plot PDP/ICE Curves for Survival Models
plot_shap | Plot SHAP-like contributions for survival models
plot_surrogate | Plot Local Surrogate Explanation
plot_survmat | Plot Predicted Survival Curves from a survmat
plot_survmetalearner_weights | Plot Time‑Varying Stacking Weights
plot_tree_surrogate | Plot Tree-Based Surrogate Models or Feature Importances
plot_varimp | Plot Permutation Variable Importance
predict_aalen | Predict Survival from an Aalen Additive Hazards Model
predict_aftgee | Predict Survival Probabilities from an 'aftgee' Model
predict_bart | Predict Survival Probabilities from a BART Survival Model
predict_blackboost | Predict Survival Probabilities from a blackboost Model
predict_bnnsurv | Predict Survival with a bnnSurvival Model
predict_cforest | Predict Survival Probabilities from a Conditional Inference Survival Forest
predict_coxph | Predict Survival Probabilities from a Cox PH Model
predict_flexsurvreg | Predict Survival Probabilities from a flexsurvreg Model
predict_glmnet | Predict Survival Probabilities from a Penalized Cox Model (glmnet)
predict_orsf | Predict Survival Probabilities from an ORSF Model
predict_ranger | Predict Survival Probabilities from a ranger Model
predict_rpart | Predict Survival Probabilities from an 'rpart' Survival Tree
predict_rsf | Predict Survival Probabilities from an RSF Model
predict_selectcox | Predict Survival Probabilities with a Selected Cox Model
predict_stpm2 | Predict Survival Probabilities with an rstpm2 Model
predict_survdnn | Predict Survival Probabilities with a DNN Survival Model
predict_survmetalearner | Predict with a Stacked Survival Meta‑Learner
predict_survsvm | Predict Survival Probabilities with Survival SVM
predict_xgboost | Predict Survival with XGBoost
score_survmodel | Score a Fitted Survival Model on Its Training Data
summarise_benchmark | Summarise Benchmark Results (Mean SD with Wald CI)
summarize_benchmark_results | Compact Table of Mean SD by Learner and Metric
summary.mlsurv_model | Summarize an 'mlsurv_model'
survmat_to_chf | Convert a survival-probability matrix (survmat) to cumulative hazard
survmat_to_haz | Convert a survival-probability matrix (survmat) to hazards on a time grid
survmat_to_quantile | Compute a survival-time quantile from a survival-probability matrix (survmat) with grid-based approach
survmat_to_rmst | Compute restricted mean survival time (RMST) from a survival-probability matrix (survmat)
tune_bart | Tune BART Survival Hyperparameters (Cross-Validation)
tune_blackboost | Tune blackboost Hyperparameters (Cross-Validation)
tune_bnnsurv | Tune bnnSurvival Hyperparameters (Cross-Validation)
tune_cforest | Tune a Conditional Inference Survival Forest
tune_flexsurvreg | Tune Parametric Survival Models with flexsurvreg
tune_glmnet | Tune Penalized Cox Proportional Hazards Model via Cross-Validation
tune_orsf | Tune Oblique Random Survival Forests (ORSF) via Cross-Validation
tune_ranger | Hyperparameter Tuning for ranger Survival Models
tune_rpart | Tune a Survival Tree Model ('rpart') via Cross-Validation
tune_rsf | Tune Random Survival Forest Hyperparameters (Cross-Validation)
tune_selectcox | Tune SelectCox Rule (Cross-Validation)
tune_survdnn | Tune Deep Neural Network Survival Models (Cross-Validation)
tune_survsvm | Tune Survival SVM Hyperparameters (Cross-Validation)
tune_xgboost | Tune XGBoost Survival Hyperparameters (Cross-Validation)
veteran | Veteran's Administration Lung Cancer Trial Data