break_down: Model Agnostic Experimental Approach to Break Down Plots with...

In pbiecek/breakDown: Model Agnostic Explainers for Individual Predictions

Model Agnostic Experimental Approach to Break Down Plots with Interactions

Description

This function implements decomposition of model predictions with identification of interactions. The complexity of this function is O(2*p) for additive models and O(2*p^2) for interactions. This function works in similar way to step-up and step-down greedy approaximations, the main difference is that in the fisrt step the order of variables is determied. And in the second step the impact is calculated.

Usage

break_down(
  explainer,
  new_observation,
  check_interactions = TRUE,
  keep_distributions = FALSE
)

Arguments

explainer	a model to be explained, preprocessed by function 'DALEX::explain()'.
new_observation	a new observation with columns that corresponds to variables used in the model
check_interactions	the orgin/baseline for the 'breakDown“ plots, where the rectangles start. It may be a number or a character "Intercept". In the latter case the orgin will be set to model intercept.
keep_distributions	if TRUE, then the distribution of partial predictions is stored in addition to the average.

Value

an object of the broken class

Examples

## Not run: 
library("DALEX")
library("breakDown")
library("randomForest")
set.seed(1313)
# example with interaction
# classification for HR data
model <- randomForest(status ~ . , data = HR)
new_observation <- HRTest[1,]
data <- HR[1:1000,]
predict.function <- function(m,x) predict(m,x, type = "prob")[,1]

explainer_rf_fired <- explain(model,
                 data = HR[1:1000,1:5],
                 y = HR$status[1:1000] == "fired",
                 predict_function = function(m,x) predict(m,x, type = "prob")[,1],
                 label = "fired")

bd_rf <- break_down(explainer_rf_fired,
                 new_observation,
                 keep_distributions = TRUE)

bd_rf
plot(bd_rf)
plot(bd_rf, plot_distributions = TRUE)

bd_rf <- break_down(explainer_rf_fired,
                 new_observation,
                 check_interactions = FALSE,
                 keep_distributions = TRUE)

bd_rf
plot(bd_rf)

# example for regression - apartment prices
# here we do not have intreactions
model <- randomForest(m2.price ~ . , data = apartments)
explainer_rf <- explain(model,
         data = apartmentsTest[1:1000,2:6],
         y = apartmentsTest$m2.price[1:1000],
         label = "rf")

bd_rf <- break_down(explainer_rf,
         apartmentsTest[1,],
         check_interactions = FALSE,
         keep_distributions = TRUE)

bd_rf
plot(bd_rf)
plot(bd_rf, plot_distributions = TRUE)

## End(Not run)

pbiecek/breakDown documentation built on March 15, 2024, 10:46 a.m.