ceteris_paribus {ceterisParibus}R Documentation

Ceteris Paribus Explainer

Description

This function calculate ceteris paribus profiles for selected data points.

Usage

ceteris_paribus(
  explainer,
  observations,
  y = NULL,
  variable_splits = NULL,
  variable_splits_type = "quantiles",
  variables = NULL,
  grid_points = 101
)

Arguments

explainer

a model to be explained, preprocessed by function 'DALEX::explain()'.

observations

set of observarvation for which profiles are to be calculated

y

true labels for 'observations'. If specified then will be added to ceteris paribus plots.

variable_splits

named list of splits for variables, in most cases created with 'calculate_variable_splits()'. If NULL then it will be calculated based on validation data avaliable in the 'explainer'.

variable_splits_type

how variable grids shall be calculated? Use "quantiles" (default) for percentiles or "uniform" to get uniform grid of points

variables

names of variables for which profiles shall be calculated. Will be passed to 'calculate_variable_splits()'. If NULL then all variables from the validation data will be used.

grid_points

number of points for profile. Will be passed to 'calculate_variable_splits()'.

Value

An object of the class 'ceteris_paribus_explainer'. It's a data frame with calculated average responses.

Examples

library("DALEX")
 ## Not run: 
library("randomForest")
set.seed(59)

apartments_rf_model <- randomForest(m2.price ~ construction.year + surface + floor +
      no.rooms + district, data = apartments)

explainer_rf <- explain(apartments_rf_model,
      data = apartmentsTest[,2:6], y = apartmentsTest$m2.price)

apartments_small <- select_sample(apartmentsTest, 10)

cp_rf <- ceteris_paribus(explainer_rf, apartments_small)
cp_rf

cp_rf <- ceteris_paribus(explainer_rf, apartments_small, y = apartments_small$m2.price)
cp_rf

## End(Not run)

[Package ceterisParibus version 0.6 Index]