This release is intended to be the last before stable version 1.0.0.
Major change
Passing a background dataset bg_X
is now optional.
If the explanation data X
is sufficiently large (>= 50 rows), bg_X
is derived as a random sample of bg_n = 200
rows from X
. If X
has less than bg_n
rows, then simply
bg_X = X
. If X
has too few rows (< 50), you will have to pass an explicit bg_X
.
Minor changes
ranger()
survival models now also work out-of-the-box without passing a tailored prediction function. Use the new argumentsurvival = "chf"
inkernelshap()
andpermshap()
to distinguish cumulative hazards (default) and survival probabilities per time point.- The resulting object of
kernelshap()
andpermshap()
now containbg_X
andbg_w
used to calculate the SHAP values.