Function 'plot.single_variable_explainer' plots marginal responses for one or more explainers.

# S3 method for single_variable_explainer
plot(x, ...)

Arguments

x

a single variable exlainer produced with the 'single_variable' function

...

other explainers that shall be plotted together

Value

a ggplot2 object

Examples

library("randomForest") library("breakDown") logit <- function(x) exp(x)/(1+exp(x)) HR_glm_model <- glm(left~., data = breakDown::HR_data, family = "binomial") explainer_glm <- explain(HR_glm_model, data = HR_data) expl_glm <- single_variable(explainer_glm, "satisfaction_level", "pdp", trans=logit) plot(expl_glm)
HR_rf_model <- randomForest(left~., data = breakDown::HR_data, ntree = 100)
#> Warning: The response has five or fewer unique values. Are you sure you want to do regression?
explainer_rf <- explain(HR_rf_model, data = HR_data) expl_rf <- single_variable(explainer_rf, variable = "satisfaction_level", type = "pdp") plot(expl_rf)
plot(expl_rf, expl_glm)