additive_shap: Additive SHAP

In kernelshap: Kernel SHAP

Additive SHAP

Description

Exact additive SHAP assuming feature independence. The implementation works for models fitted via

• lm(),

• glm(),

• mgcv::gam(),

• mgcv::bam(),

• gam::gam(),

• survival::coxph(), and

• survival::survreg().

Usage

additive_shap(object, X, verbose = TRUE, ...)

Arguments

object	Fitted model object.
X	Dataframe with rows to be explained. Will be used like predict(object, newdata = X, type = "terms").
verbose	Set to FALSE to suppress messages and the progress bar.
...	Currently unused.

Details

The SHAP values are extracted via predict(object, newdata = X, type = "terms"), a logic heavily inspired by fastshap:::explain.lm(..., exact = TRUE). Models with interactions (specified via : or *), or with terms of multiple features like log(x1/x2) are not supported.

Value

An object of class "kernelshap" with the following components:

• S: (n \times p) matrix with SHAP values.

• X: Same as input argument X.

• baseline: The baseline.

• exact: TRUE.

• txt: Summary text.

• predictions: Vector with predictions of X on the scale of "terms".

• algorithm: "additive_shap".

Examples

# MODEL ONE: Linear regression
fit <- lm(Sepal.Length ~ ., data = iris)
s <- additive_shap(fit, head(iris))
s

# MODEL TWO: More complicated (but not very clever) formula
fit <- lm(
  Sepal.Length ~ poly(Sepal.Width, 2) + log(Petal.Length) + log(Sepal.Width),
  data = iris
)
s <- additive_shap(fit, head(iris))
s

kernelshap documentation built on May 29, 2024, 12:34 p.m.