In parsnip: A Common API to Modeling and Analysis Functions

Since risk regression and parametric survival models are modeling different characteristics (e.g. relative hazard versus event time), their linear predictors will be going in opposite directions.

For example, for parametric models, the linear predictor increases with time. For proportional hazards models the linear predictor decreases with time (since hazard is increasing). As such, the linear predictors for these two quantities will have opposite signs.

tidymodels does not treat different models differently when computing performance metrics. To standardize across model types, the default for proportional hazards models is to have increasing values with time. As a result, the sign of the linear predictor will be the opposite of the value produced by the predict() method in the engine package.

This behavior can be changed by using the increasing argument when calling predict() on a \pkg{parsnip} model object.