ceterisParibus (version 0.4.2)

calculate_profiles_lce: Calculate Local Conditional Expectation profiles

Description

This function Local Conditional Expectation profiles

Usage

calculate_profiles_lce(
  data,
  variable_splits,
  model,
  dataset,
  predict_function = predict,
  ...
)

Value

a data frame with profiles for selected variables and selected observations

Arguments

data

set of observations. Profile will be calculated for every observation (every row)

variable_splits

named list of vectors. Elements of the list are vectors with points in which profiles should be calculated. See an example for more details.

model

a model that will be passed to the predict_function

dataset

a data.frame, usually training data of a model, used for calculation of LCE profiles

predict_function

function that takes data and model and returns numeric predictions. Note that the ... arguments will be passed to this function.

...

other parameters that will be passed to the predict_function

Details

Note that calculate_profiles_lce function is S3 generic. If you want to work on non standard data sources (like H2O ddf, external databases) you should overload it.

Examples

library("DALEX")
 if (FALSE) {
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 = apartments[,2:6], y = apartments$m2.price)
vars <- c("construction.year", "surface", "floor", "no.rooms", "district")
variable_splits <- calculate_variable_splits(apartments, vars)
new_apartment <- apartments[1, ]

profiles <- calculate_profiles_lce(new_apartment, variable_splits,
                               apartments_rf_model, explainer_rf$data)
profiles
}