light_effects {flashlight}

Combination of Response, Predicted, Partial Dependence, and ALE profiles.

Description

Calculates response- prediction-, partial dependence, and ALE profiles of a (multi-)flashlight with respect to a covariable v.

Usage

light_effects(x, ...)

## Default S3 method:
light_effects(x, ...)

## S3 method for class 'flashlight'
light_effects(
  x,
  v,
  data = NULL,
  by = x$by,
  stats = c("mean", "quartiles"),
  breaks = NULL,
  n_bins = 11L,
  cut_type = c("equal", "quantile"),
  use_linkinv = TRUE,
  counts_weighted = FALSE,
  v_labels = TRUE,
  pred = NULL,
  pd_indices = NULL,
  pd_n_max = 1000L,
  pd_seed = NULL,
  ale_two_sided = TRUE,
  ...
)

## S3 method for class 'multiflashlight'
light_effects(
  x,
  v,
  data = NULL,
  breaks = NULL,
  n_bins = 11L,
  cut_type = c("equal", "quantile"),
  ...
)

Arguments

x

An object of class "flashlight" or "multiflashlight".

...

Further arguments passed to cut3() in forming the cut breaks of the v variable.

v

The variable name to be profiled.

data

An optional data.frame. Not used for type = "shap".

by

An optional vector of column names used to additionally group the results.

stats

Statistic to calculate for the response profile: "mean" or "quartiles".

breaks

Cut breaks for a numeric v. Used to overwrite automatic binning via n_bins and cut_type. Ignored if v is not numeric.

n_bins

Approximate number of unique values to evaluate for numeric v. Ignored if v is not numeric or if breaks is specified.

cut_type

Should a numeric v be cut into "equal" or "quantile" bins? Ignored if v is not numeric or if breaks is specified.

use_linkinv

Should retransformation function be applied? Default is TRUE. Not used for type "shap".

counts_weighted

Should counts be weighted by the case weights? If TRUE, the sum of w is returned by group.

v_labels

If FALSE, return group centers of v instead of labels. Only relevant if v is numeric with many distinct values. In that case useful for instance when different flashlights use different data sets.

pred

Optional vector with predictions (after application of inverse link). Can be used to avoid recalculation of predictions over and over if the functions is to be repeatedly called for different v and predictions are computationally expensive to make. Not implemented for multiflashlight.

pd_indices

A vector of row numbers to consider in calculating partial dependence profiles and "ale".

pd_n_max

Maximum number of ICE profiles to calculate (will be randomly picked from data) for partial dependence and ALE.

pd_seed

Integer random seed used to select ICE profiles for partial dependence and ALE.

ale_two_sided

If TRUE, v is continuous and breaks are passed or being calculated, then two-sided derivatives are calculated for ALE instead of left derivatives. More specifically: Usually, local effects at value x are calculated using points in [x-e, x]. Set ale_two_sided = TRUE to use points in [x-e/2, x+e/2].

Details

Note that ALE profiles are being calibrated by (weighted) average predictions. The resulting level might be quite different from the one of the partial dependence profiles.

Value

An object of class "light_effects" with the following elements:

• response: A tibble containing the response profiles. Column names can be controlled by options(flashlight.column_name).

• predicted: A tibble containing the prediction profiles.

• pd: A tibble containing the partial dependence profiles.

• ale: A tibble containing the ALE profiles.

• by: Same as input by.

• v: The variable(s) evaluated.

• stats: Same as input stats.

Methods (by class)

• light_effects(default): Default method.

• light_effects(flashlight): Profiles for a flashlight object.

• light_effects(multiflashlight): Effect profiles for a multiflashlight object.

See Also

light_profile(), plot.light_effects()

Examples

fit <- lm(Sepal.Length ~ ., data = iris)
fl <- flashlight(model = fit, label = "iris", data = iris, y = "Sepal.Length")
light_effects(fl, v = "Species")