Function `show_residuals`

adds a layer to a plot created with
`plot.ceteris_paribus_explainer`

for selected observations.
Note that the `y`

argument has to be specified in the `ceteris_paribus`

function.

show_residuals( x, ..., size = 0.75, alpha = 1, color = c(`TRUE` = "#8bdcbe", `FALSE` = "#f05a71"), variables = NULL )

x | a ceteris paribus explainer produced with function |
---|---|

... | other explainers that shall be plotted together |

size | a numeric. Size of lines to be plotted |

alpha | a numeric between |

color | a character. Either name of a color or name of a variable that should be used for coloring |

variables | if not |

a `ggplot2`

layer

Explanatory Model Analysis. Explore, Explain, and Examine Predictive Models. https://ema.drwhy.ai/

library("DALEX") library("ingredients") library("ranger") johny_d <- data.frame( class = factor("1st", levels = c("1st", "2nd", "3rd", "deck crew", "engineering crew", "restaurant staff", "victualling crew")), gender = factor("male", levels = c("female", "male")), age = 8, sibsp = 0, parch = 0, fare = 72, embarked = factor("Southampton", levels = c("Belfast", "Cherbourg", "Queenstown", "Southampton")) ) # \donttest{ model_titanic_rf <- ranger(survived ~., data = titanic_imputed, probability = TRUE) explain_titanic_rf <- explain(model_titanic_rf, data = titanic_imputed[,-8], y = titanic_imputed[,8], label = "ranger forest", verbose = FALSE) johny_neighbours <- select_neighbours(data = titanic_imputed, observation = johny_d, variables = c("age", "gender", "class", "fare", "sibsp", "parch"), n = 10) cp_neighbours <- ceteris_paribus(explain_titanic_rf, johny_neighbours, y = johny_neighbours$survived == "yes", variable_splits = list(age = seq(0,70, length.out = 1000))) plot(cp_neighbours, variables = "age") + show_observations(cp_neighbours, variables = "age")cp_johny <- ceteris_paribus(explain_titanic_rf, johny_d, variable_splits = list(age = seq(0,70, length.out = 1000))) plot(cp_johny, variables = "age", size = 1.5, color = "#8bdcbe") + show_profiles(cp_neighbours, variables = "age", color = "#ceced9") + show_observations(cp_johny, variables = "age", size = 5, color = "#371ea3") + show_residuals(cp_neighbours, variables = "age")# }