wf = WeibullAFTFitter().fit(df, "duration")exception throw
idcol in your model
from lifelines import WeibullAFTFitter from lifelines.datasets import load_rossi rossi_dataset = load_rossi() aft = WeibullAFTFitter() aft.fit(rossi_dataset, duration_col='week', event_col='arrest') X = rossi_dataset.loc[:10] aft.predict_survival_function(X)
@julianspaeth depends on the model. Recall that the c-index only depends on ranking of values. For the Cox model, the summing the cumulative hazard won't change the ranking, so it won't matter what you use. For an AFT model, it may change the ranking.
Alternatively, you can choose a point in time, and use the CHF at that