breakDown (version 0.2.2)

broken.default: Model Agnostic Approach to Breaking Down of Model Predictions

Description

This function implements two greedy strategies for decompositions of model predictions (see the direction parameter). Both stategies are model agnostic, they are greedy but in most cases they give very similar results. Find more information about these strategies in https://arxiv.org/abs/1804.01955.

Usage

# S3 method for default
broken(
  model,
  new_observation,
  data,
  direction = "up",
  ...,
  baseline = 0,
  keep_distributions = FALSE,
  predict.function = predict
)

Value

an object of the broken class

Arguments

model

a model, it can be any predictive model, find examples for most popular frameworks in vigniettes

new_observation

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

data

the original data used for model fitting, should have same collumns as the 'new_observation'.

direction

either 'up' or 'down' determined the exploration strategy

...

other parameters

baseline

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.

predict.function

function that will calculate predictions out of model. It shall return a single numeric value per observation. For classification it may be a probability of the default class.

Examples

if (FALSE) {
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")
}