break_down {breakDown} | R Documentation |

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.

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

`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. |

an object of the broken class

```
## 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)
```

[Package *breakDown* version 0.2.1 Index]