broken {breakDown}

Generic Function for Breaking Down of Model Predictions

Description

The broken function is a generic function for decomposition of model predictions. For linear models please use broken.lm, for generic linear models please use broken.glm. For all other models please use the model agnostic version broken.default. Please note, that some of these functions have additional parameters.

Usage

broken(model, new_observation, ...)

Arguments

model

a model

new_observation

a new observation with columns that corresponds to variables used in the model

...

other parameters

Value

an object of the broken class

Examples

## Not run: 
library("breakDown")
library("randomForest")
library("ggplot2")
set.seed(1313)
model <- randomForest(factor(left)~., data = HR_data, family = "binomial", maxnodes = 5)
predict.function <- function(model, new_observation)
      predict(model, new_observation, type="prob")[,2]
predict.function(model, HR_data[11,-7])
explain_1 <- broken(model, HR_data[11,-7], data = HR_data[,-7],
predict.function = predict.function, direction = "down")
explain_1
plot(explain_1) + ggtitle("breakDown plot (direction=down) for randomForest model")

explain_2 <- broken(model, HR_data[11,-7], data = HR_data[,-7],
predict.function = predict.function, direction = "down", keep_distributions = TRUE)
plot(explain_2, plot_distributions = TRUE) +
         ggtitle("breakDown distributions (direction=down) for randomForest model")

explain_3 <- broken(model, HR_data[11,-7], data = HR_data[,-7],
predict.function = predict.function, direction = "up", keep_distributions = TRUE)
plot(explain_3, plot_distributions = TRUE) +
         ggtitle("breakDown distributions (direction=up) for randomForest model")

## End(Not run)