sv_dependence2D {shapviz}

2D SHAP Dependence Plot

Description

Scatterplot of two features, showing the sum of their SHAP values on the color scale. This allows to visualize the combined effect of two features, including interactions. A typical application are models with latitude and longitude as features (plus maybe other regional features that can be passed via add_vars).

If SHAP interaction values are available, setting interactions = TRUE allows to focus on pure interaction effects (multiplied by two). In this case, add_vars has no effect.

Usage

sv_dependence2D(object, ...)

## Default S3 method:
sv_dependence2D(object, ...)

## S3 method for class 'shapviz'
sv_dependence2D(
  object,
  x,
  y,
  viridis_args = getOption("shapviz.viridis_args"),
  jitter_width = NULL,
  jitter_height = NULL,
  interactions = FALSE,
  add_vars = NULL,
  ...
)

## S3 method for class 'mshapviz'
sv_dependence2D(
  object,
  x,
  y,
  viridis_args = getOption("shapviz.viridis_args"),
  jitter_width = NULL,
  jitter_height = NULL,
  interactions = FALSE,
  add_vars = NULL,
  ...
)

Arguments

object

An object of class "(m)shapviz".

...

Arguments passed to ggplot2::geom_jitter().

x

Feature name for x axis. Can be a vector/list if object is of class "shapviz".

y

Feature name for y axis. Can be a vector/list if object is of class "shapviz".

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.

jitter_height

Similar to jitter_width for vertical scatter.

interactions

Should SHAP interaction values be plotted? The default (FALSE) will show the rowwise sum of the SHAP values of x and y. If TRUE, will use twice the SHAP interaction value (requires SHAP interactions).

add_vars

Optional vector of feature names, whose SHAP values should be added to the sum of the SHAP values of x and y (only if interactions = FALSE). A use case would be a model with geographic x and y coordinates, along with some additional locational features like distance to the next train station.

Value

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

Methods (by class)

• sv_dependence2D(default): Default method.

• sv_dependence2D(shapviz): 2D SHAP dependence plot for "shapviz" object.

• sv_dependence2D(mshapviz): 2D SHAP dependence plot for "mshapviz" object.

See Also

sv_dependence()

Examples

dtrain <- xgboost::xgb.DMatrix(
  data.matrix(iris[, -1]), label = iris[, 1], nthread = 1
)
fit <- xgboost::xgb.train(data = dtrain, nrounds = 10, nthread = 1)
sv <- shapviz(fit, X_pred = dtrain, X = iris)
sv_dependence2D(sv, x = "Petal.Length", y = "Species")
sv_dependence2D(sv, x = c("Petal.Length", "Species"), y = "Sepal.Width")

# SHAP interaction values
sv2 <- shapviz(fit, X_pred = dtrain, X = iris, interactions = TRUE)
sv_dependence2D(sv2, x = "Petal.Length", y = "Species", interactions = TRUE)
sv_dependence2D(
  sv2, x = "Petal.Length", y = c("Species", "Petal.Width"), interactions = TRUE
)

# mshapviz object
mx <- split(sv, f = iris$Species)
sv_dependence2D(mx, x = "Petal.Length", y = "Sepal.Width")