ceteris_paribus {ceterisParibus}

Ceteris Paribus Explainer

Description

This function calculate ceteris paribus profiles for selected data points.

Usage

ceteris_paribus(
  explainer,
  observations,
  y = NULL,
  variable_splits = NULL,
  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'.

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)