calculate_profiles_lce {ceterisParibus} R Documentation

## Calculate Local Conditional Expectation profiles

### Description

This function Local Conditional Expectation profiles

### Usage

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


### 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.

### Value

a data frame with profiles for selected variables and selected observations

### 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 = 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

## End(Not run)


[Package ceterisParibus version 0.4.2 Index]