sv_dependence: SHAP Dependence Plot

In shapviz: SHAP Visualizations

SHAP Dependence Plot

Description

Scatterplot of the SHAP values of a feature against its feature values. If SHAP interaction values are available, setting interactions = TRUE allows to focus on pure interaction effects (multiplied by two) or on pure main effects.

Usage

sv_dependence(object, ...)

## Default S3 method:
sv_dependence(object, ...)

## S3 method for class 'shapviz'
sv_dependence(
  object,
  v,
  color_var = "auto",
  color = "#3b528b",
  viridis_args = getOption("shapviz.viridis_args"),
  jitter_width = NULL,
  interactions = FALSE,
  ...
)

## S3 method for class 'mshapviz'
sv_dependence(
  object,
  v,
  color_var = "auto",
  color = "#3b528b",
  viridis_args = getOption("shapviz.viridis_args"),
  jitter_width = NULL,
  interactions = FALSE,
  ...
)

Arguments

object	An object of class "(m)shapviz".
...	Arguments passed to ggplot2::geom_jitter().
v	Column name of feature to be plotted. Can be a vector/list if object is of class "shapviz".
color_var	Feature name to be used on the color scale to investigate interactions. The default ("auto") uses SHAP interaction values (if available), or a heuristic to select the strongest interacting feature. Set to NULL to not use the color axis. Can be a vector/list if object is of class "shapviz".
color	Color to be used if color_var = NULL. Can be a vector/list if v is a vector.
viridis_args	List of viridis color scale arguments, see ?ggplot2::scale_color_viridis_c. The default points to the global option shapviz.viridis_args, which corresponds to list(begin = 0.25, end = 0.85, option = "inferno"). These values are passed to ⁠ggplot2::scale_color_viridis_*()⁠. For example, to switch to a standard viridis scale, you can either change the default via options(shapviz.viridis_args = list()), or set viridis_args = list(). Only relevant if color_var is not NULL.
jitter_width	The amount of horizontal jitter. The default (NULL) will use a value of 0.2 in case v is discrete, and no jitter otherwise. (Numeric variables are considered discrete if they have at most 7 unique values.) Can be a vector/list if v is a vector.
interactions	Should SHAP interaction values be plotted? Default is FALSE. Requires SHAP interaction values. If color_var = NULL (or it is equal to v), the pure main effect of v is visualized. Otherwise, twice the SHAP interaction values between v and the color_var are plotted.

Value

An object of class "ggplot" (or "patchwork") representing a dependence plot.

Methods (by class)

• sv_dependence(default): Default method.

• sv_dependence(shapviz): SHAP dependence plot for "shapviz" object.

• sv_dependence(mshapviz): SHAP dependence plot for "mshapviz" object.

See Also

potential_interactions()

Examples

## Not run: 
dtrain <- xgboost::xgb.DMatrix(data.matrix(iris[, -1]), label = iris[, 1])
fit <- xgboost::xgb.train(data = dtrain, nrounds = 10, nthread = 1)
x <- shapviz(fit, X_pred = dtrain, X = iris)
sv_dependence(x, "Petal.Length")
sv_dependence(x, "Petal.Length", color_var = "Species")
sv_dependence(x, "Petal.Length", color_var = NULL)
sv_dependence(x, c("Species", "Petal.Length"))
sv_dependence(x, "Petal.Width", color_var = c("Species", "Petal.Length"))

# SHAP interaction values/main effects
x2 <- shapviz(fit, X_pred = dtrain, X = iris, interactions = TRUE)
sv_dependence(x2, "Petal.Length", interactions = TRUE)
sv_dependence(
  x2, c("Petal.Length", "Species"), color_var = NULL, interactions = TRUE
)

## End(Not run)

shapviz documentation built on Oct. 14, 2023, 5:07 p.m.