Local Fit / Wangkardu Explanations

local_fit(explainer, observation, selected_variable, grid_points = 101,
  select_points = 0.1)

Arguments

explainer

a model to be explained, preprocessed by the 'DALEX::explain' function

observation

a new observarvation for which predictions need to be explained

selected_variable

variable to be presented in the local fit plot

grid_points

number of points used for response path

select_points

fraction of points fromvalidation data to be presented in local fit plots

Value

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

Examples

library("DALEX")
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) new_apartment <- apartmentsTest[1, ] new_apartment
#> m2.price construction.year surface floor no.rooms district #> 1001 4644 1976 131 3 5 Srodmiescie
cr_rf <- local_fit(explainer_rf, observation = new_apartment, select_points = 0.002, selected_variable = "surface") cr_rf
#> y_hat new_x vname quant obs_id label #> 1001 4768.305 20 surface 0.00 0 randomForest #> 1001.1 4765.291 21 surface 0.01 0 randomForest #> 1001.2 4761.576 23 surface 0.02 0 randomForest #> 1001.3 4760.838 24 surface 0.03 0 randomForest #> 1001.4 4760.290 26 surface 0.04 0 randomForest #> 1001.5 4743.734 27 surface 0.05 0 randomForest