Binary Inductive calibration | Binary Cross calibration: retain the fold models | Multiclass: one-vs-one and one-vs-rest | Regression: moderated Inductive and Cross calibration | Keeping the complete predictor

Fit diagnoses: the stored state | Assessment graphics: held-out pairs | CORP reliability diagrams | CORP bands are not Venn-Abers bounds | Brier decomposition | Regression predictions | Further reading

Choose an example | Running an example | Binary Grid selection | Shared multiclass Grid selection | Shared multiclass Bayes selection | Pairwise OvO Grid selection | Pairwise OvO Bayes selection | Regression Grid selection | Regression Bayes selection | Grid selection with postprocessing | Bayes selection with postprocessing

Choose an example | Running an example | Binary Sigmoid holdouts | Binary Tailor holdouts | Shared multiclass Tailor holdouts | Regression Tailor holdouts | Regression isotonic holdouts | Binary postprocessing ensembles | Shared multiclass postprocessing ensembles | Regression postprocessing ensembles | Pairwise OvO postprocessing | Full-model postprocessing compositions

Choose an example | Running an example | Binary precision, loss and event selection | Binary Cross calibration with retained models | Inductive multiclass one-vs-one | Inductive multiclass one-vs-rest | Cross multiclass calibration | One-hot class decisions | Inductive regression | Cross regression | Fit diagnoses and assessment graphics

Choose an example | Running an example | Training binary and shared multiclass workflows | Encoding binary names | Encoding multiclass and regression names | Reference-style data roles | Independent Inductive training and calibration sizes | Own fit and predict functions | Fixed engine options and internal validation | Binary full-model transfer | Shared multiclass full-model transfer | Regression full-model transfer | Pairwise Inductive OvO training | Pairwise Cross OvO training | Calibrating a frozen binary workflow | Calibrating frozen multiclass and regression workflows | Keeping the original schema for frozen adoption

Choose a learning path | A complete binary workflow | Cross, matched models and full-model transfer | Multiclass: calibration method versus model training | Regression workflows | Frozen workflows: calibrate without retraining | Learning a postprocessor before Venn-Abers | Engine options and model-internal validation | Names, assessment and next steps

Data roles and search strategies | Joint Grid selection | Two-stage Grid selection | A small Bayes model search | Outer resampling and final assessment | Extending the same pattern

Calibration as a problem | Inductive Venn-Abers | What the validity guarantee says | One probability from two | Cross Venn-Abers | Multiclass calibration | Regression | In practice | References

Data and their roles | Three calibration maps | Results | A contrast: a well-specified model | What this does and does not show | References