broken.glm: Breaking Down of Model Predictions for glm models

In breakDown: Model Agnostic Explainers for Individual Predictions

Description

Breaking Down of Model Predictions for glm models

Usage

## S3 method for class 'glm'
broken(
  model,
  new_observation,
  ...,
  baseline = 0,
  predict.function = stats::predict.glm
)

Arguments

model	a glm model
new_observation	a new observation with columns that corresponds to variables used in the model
...	other parameters
baseline	the origin/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.
predict.function	function that will calculate predictions out of model (typically predict or betas)

Value

an object of the broken class

Examples

# example for wine data
wine$qualityb <- factor(wine$quality > 5.5, labels = c("bad", "good"))
modelg <- glm(qualityb~fixed.acidity + volatile.acidity + citric.acid +
              residual.sugar + chlorides + free.sulfur.dioxide +
              total.sulfur.dioxide + density + pH + sulphates + alcohol,
    data=wine, family = "binomial")
new_observation <- wine[1,]
br <- broken(modelg, new_observation)
logit <- function(x) exp(x)/(1+exp(x))
plot(br, logit)

# example for HR_data
model <- glm(left~., data = HR_data, family = "binomial")
explain_1 <- broken(model, HR_data[1,])
explain_1
plot(explain_1)
plot(explain_1, trans = function(x) exp(x)/(1+exp(x)))

explain_2 <- broken(model, HR_data[1,], predict.function = betas)
explain_2
plot(explain_2, trans = function(x) exp(x)/(1+exp(x)))

Example output

                           contribution
(Intercept)                      -1.601
satisfaction_level = 0.38         0.963
number_project = 2                0.568
salary = low                      0.388
Work_accident = 0                 0.221
average_montly_hours = 157       -0.196
last_evaluation = 0.53           -0.136
time_spend_company = 3           -0.133
promotion_last_5years = 0         0.030
sales = sales                     0.014
final_prognosis                   0.118
baseline:  0 
                           contribution
(Intercept)                      -1.476
salary = low                      1.944
satisfaction_level = 0.38        -1.572
time_spend_company = 3            0.803
average_montly_hours = 157        0.700
number_project = 2               -0.630
last_evaluation = 0.53            0.387
sales = sales                    -0.039
Work_accident = 0                 0.000
promotion_last_5years = 0         0.000
final_prognosis                   0.118
baseline:  0 

breakDown documentation built on Jan. 20, 2021, 5:06 p.m.