Automatic selection of background data

[mayer79]

A pain-point in using {kernelshap} is the manual preparation of the background data bg_X. Most applications have a relatively large explanation data X and a model m, but no background data. It would be convenient to derive the background data automatically from X, so that a SHAP analysis would start with:

shp <- kernelshap(m, X)

Suggestion: Set the default bg_X = NULL. In this case, use this logic here:

• If nrow(X) <= 200 -> bg_X = X
• If nrow(X) < 20 -> warning("X is to small to be used as background data. Please pass a larger background data via 'bg_X'.")
• If nrow(X) > 200 -> message("X is too large to be used as background data. We randomly select 200 rows from it.") and do subsampling

If bg_X = NULL and the user wants to pass a vector of case weights bg_w, the latter would need to correspond to X (we need to subsample correspondingly)

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