Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = FALSE,
comment = "#>",
warning = FALSE,
message = FALSE
)
## -----------------------------------------------------------------------------
library("DALEX")
head(titanic_imputed)
## -----------------------------------------------------------------------------
# prepare model
library("ranger")
model_titanic_rf <- ranger(survived ~ gender + age + class + embarked +
fare + sibsp + parch,
data = titanic_imputed, probability = TRUE)
model_titanic_rf
## -----------------------------------------------------------------------------
library("DALEX")
explain_titanic_rf <- explain(model_titanic_rf,
data = titanic_imputed[,-8],
y = titanic_imputed[,8],
label = "Random Forest")
## -----------------------------------------------------------------------------
library("ingredients")
fi_rf <- feature_importance(explain_titanic_rf)
head(fi_rf)
plot(fi_rf)
## -----------------------------------------------------------------------------
pp_age <- partial_dependence(explain_titanic_rf, variables = c("age", "fare"))
head(pp_age)
plot(pp_age)
## -----------------------------------------------------------------------------
cp_age <- conditional_dependence(explain_titanic_rf, variables = c("age", "fare"))
plot(cp_age)
## -----------------------------------------------------------------------------
ap_age <- accumulated_dependence(explain_titanic_rf, variables = c("age", "fare"))
plot(ap_age)
## -----------------------------------------------------------------------------
new_passanger <- 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"))
)
sp_rf <- ceteris_paribus(explain_titanic_rf, new_passanger)
plot(sp_rf) +
show_observations(sp_rf)
## -----------------------------------------------------------------------------
plot(sp_rf,
variables = c("class", "embarked", "gender", "sibsp"),
variable_type = "categorical")
## -----------------------------------------------------------------------------
passangers <- select_sample(titanic, n = 100)
sp_rf <- ceteris_paribus(explain_titanic_rf, passangers)
clust_rf <- cluster_profiles(sp_rf, k = 3)
head(clust_rf)
plot(sp_rf, alpha = 0.1) +
show_aggregated_profiles(clust_rf, color = "_label_", size = 2)
## -----------------------------------------------------------------------------
sessionInfo()
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