Man pages for survalis
Interpretable Survival Machine Learning Framework
| compare | Compare several survival learners on shared resampling folds |
| dot-as_survalis_fit | Wrap a legacy mlsurv_model as a survalis_fit |
| dot-evaluate_splits | Shared split-loop used by evaluate() and compare() |
| dot-finalize_survmat | Standardize learner prediction output to the survmat contract |
| dot-fit_status_vector | 0/1 event vector of a fit's training data |
| dot-infer_survmat_times | Infer time points from survmat column names |
| dot-interpret_dispatch | Adaptors from interpret() method ids to compute_*()... |
| dot-make_splits | Expand a resampling specification into concrete row-index... |
| dot-parse_surv_formula | Parse a survival outcome from a model formula |
| dot-predict_cox_from_lp | Reconstruct Cox-style survival curves from linear predictors |
| dot-resolve_times | Resolve a caller-supplied 'times' argument against the... |
| dot-survmat_as_matrix | Validate and standardize a survival-probability matrix... |
| dwscore | Decision-weighted scores for survival predictions |
| estimate | Standardised causal-style contrast for a binary treatment |
| evaluate | Performance of a survival learner |
| fit | Fit a survival learner |
| interpret | Interpret a fitted survival learner |
| kmplot | Kaplan-Meier curves with a number-at-risk table |
| listlearners | List the survival learners |
| listmethods | List the interpretability methods |
| listmetrics | List the evaluation metrics |
| predict.survalis_fit | Predict from a fitted survival learner |
| reexports | Re-export Surv from survival |
| resampling | Resampling specifications for evaluate(), tune() and... |
| survalis-package | survalis: Interpretable Survival Machine Learning |
| survalis-tidiers | Tidy data frames from verb result objects |
| survmat | The survmat prediction contract |
| survmat_times | Evaluation grid of a survmat |
| tune | Tune a survival learner over a hyperparameter grid |
| veteran | Veteran's Administration Lung Cancer Trial Data |
