add_shap | R Documentation |
The function calls light_breakdown()
for n_shap
observations and adds the
resulting (approximate) SHAP decompositions as static element "shap" to the
(multi)-flashlight for further analyses.
add_shap(x, ...)
## Default S3 method:
add_shap(x, ...)
## S3 method for class 'flashlight'
add_shap(
x,
v = NULL,
visit_strategy = c("permutation", "importance", "v"),
n_shap = 200,
n_max = Inf,
n_perm = 12,
seed = NULL,
use_linkinv = FALSE,
verbose = TRUE,
...
)
## S3 method for class 'multiflashlight'
add_shap(x, ...)
x |
An object of class "flashlight" or "multiflashlight". |
... |
Further arguments passed from or to other methods. |
v |
Vector of variables to assess contribution for. Defaults to all except those specified by "y", "w" and "by". |
visit_strategy |
In what sequence should variables be visited? By |
n_shap |
Number of SHAP decompositions to calculate. |
n_max |
Maximum number of rows in |
n_perm |
Number of permutations of random visit sequences.
Only used if |
seed |
An integer random seed. |
use_linkinv |
Should retransformation function be applied?
We suggest to keep the default ( |
verbose |
Should progress bar be shown? Default is |
We offer two approximations to SHAP: For visit_strategy = "importance"
,
the breakdown algorithm (see reference) is used with importance based visit order.
Use the default visit_strategy = "permutation"
to run breakdown for
multiple random permutations, averaging the results.
This approximation will be closer to exact SHAP values, but very slow.
Most available arguments can be chosen to reduce computation time.
An object of class "flashlight" or "multiflashlight" with additional element "shap" of class "shap" (and "list").
add_shap(default)
: Default method not implemented yet.
add_shap(flashlight)
: Variable attribution to single observation for a flashlight.
add_shap(multiflashlight)
: Add SHAP to multiflashlight.
A. Gosiewska and P. Biecek (2019). IBREAKDOWN: Uncertainty of model explanations for non-additive predictive models. ArXiv <arxiv.org/abs/1903.11420>.
## Not run:
fit <- lm(Sepal.Length ~ . + Petal.Length:Species, data = iris)
x <- flashlight(model = fit, label = "lm", data = iris, y = "Sepal.Length")
x <- add_shap(x)
is.shap(x$shap)
plot(light_importance(x, type = "shap"))
plot(light_scatter(x, type = "shap", v = "Petal.Length"))
plot(light_scatter(x, type = "shap", v = "Petal.Length", by = "Species"))
## End(Not run)
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