Package index

Verbs

Fit a learner, predict, evaluate, compare, tune, interpret and estimate contrasts from one formula and one dataset. Every learner, built in or your own, goes in model.

fit()

Fit a survival learner

predict(<survalis_fit>)

Predict from a fitted survival learner

evaluate()

Performance of a survival learner

compare()

Compare several survival learners on shared resampling folds

tune()

Tune a survival learner over a hyperparameter grid

interpret()

Interpret a fitted survival learner

estimate()

Standardised causal-style contrast for a binary treatment

as.data.frame(<survmat>) as.data.frame(<survalis_fit>) as.data.frame(<survalis_eval>) as.data.frame(<survalis_tune>) as.data.frame(<survalis_compare>) as.data.frame(<survalis_estimate>)

Tidy data frames from verb result objects

survalis survalis-package

survalis: Interpretable Survival Machine Learning

Resampling

Split schemes used by evaluate(), compare(), tune() and estimate().

cv() holdout() groupcv() bootstrap()

Resampling specifications for evaluate(), tune() and compare()

Scores

Decision-weighted scores over stated risk thresholds.

dwscore()

Decision-weighted scores for survival predictions

Plots

Kaplan-Meier, cumulative incidence and model-adjusted curves with a number-at-risk table.

kmplot()

Kaplan-Meier curves with a number-at-risk table

Lookups

Valid ids for model, metrics and method.

listlearners()

List the survival learners

listmetrics()

List the evaluation metrics

listmethods()

List the interpretability methods

Data and re-exports

veteran

Veteran's Administration Lung Cancer Trial Data

reexports Surv

Re-export Surv from survival